Patent ID: 12192432

DETAILED DESCRIPTION

Certain terminology is used herein for convenience only and is not to be taken as a limitation on the present disclosure. As used herein, the words “image” or “print’ are used equivalently and mean that whatever indicium or indicia is or are created directly or indirectly on any substrate or surface may be done by any known imaging or printing method or equipment. Likewise, “imaging” or “printing” describing a method and “imaged” or “printed” describing the resulting indicium or indicia are used equivalently and correspondingly to “image” or “print.”

The words “a” and “an”, are meant to include “at least one.” The terms “scratch-off game piece” or other “scratch-off document,” hereinafter is referred to generally as an “instant ticket” or simply “ticket.” The terms “full-color” and “process color” are also used interchangeably as terms of convenience for producing a variety of colors by discrete combinations of applications of pigmented primary inks or dyes “CMYK” (i.e., Cyan, Magenta, Yellow, and black), or in some cases six colors (e.g., Hexachrome printing process uses CMYK inks plus Orange and Green inks), or alternatively eight colors—e.g., CMYK plus lighter shades of cyan (LC), magenta (LM), yellow (LY), and black (YK).

The term “composite color” refers to two or more of the individual colors used to comprise an overall “process color” with the term “component color” referring to one individual color that is used with at least one other component color to create a combined “composite” or “process” color. The term “spot color” as used herein refers to a color that is intended to be printed and displayed by itself and not intended to be utilized as a “composite color” or “process color”. An example of two “spot colors” is provided inFIG.1Bcomprised of red as indicated by numerals103and104and black as indicated by numerals105and106“spot colors.”

The terms “multi” or “multiple” or similar terms means at least two, and may also mean three, four, or more, for example, unless otherwise indicated in the context of the use of the terms. The term “variable” indicium or indicia refers to imaged indicia which indicates information relating a property, such as, without limit, a value of the document, for example, a lottery ticket, coupon, commercial game piece or the like, where the variable indicium or indicia is or are typically hidden by a Scratch-Off Coating (SOC) until the information or value is authorized to be seen, such as by a purchaser of the document who scratches off the SOC, revealing the variable indicium or indicia. Examples of variable indicium as a printed embodiment include letters, numbers, icons, or figures. The terms “lottery scratch-off ticket”, “commercial contest scratch ticket”, “telephone card account number card”, “scratch-off gift cards”, or simply “scratch-off card” for convenience are all referred to as an “instant ticket” or more simply “ticket” throughout the present disclosure.

The terms “subtractive color” and “additive color” models define two different color systems dependent on the medium referenced. “Subtractive color” predicts the spectral power distribution of light after it passes through successive layers of partially absorbing media. “Subtractive color” is the model of how dyes and inks are used in color printing and photography where the perception of color is elicited after white light passes through microscopic layers of partially absorbing media allowing some wavelengths of light to reach the eye and not others. The three primary “subtractive colors” are: Cyan, Magenta, and Yellow (CMY). “Additive color” is the color model that predicts the appearance of colors made by coincident component lights with distinct colors. In other words, “additive color” predicts perception and not any sort of change in the photons of light themselves. The three primary “additive colors” are: Red, Green, and Blue (RGB).

Before describing the present disclosure, it is useful to first provide a brief description of how the human eye perceives color via photoreceptor cones to ensure that a common lexicon is established. This description of how human eyes perceive color via photoreceptor cones is provided in the discussions ofFIGS.2Athru2C.

By definition, visible (white) light is the part of the electromagnetic spectrum (i.e., wavelengths between 380 nano meters or “nm” to 760 nm) that the human eye can detect. Thus, visible white light (e.g., sunlight) is comprised of all the colors that can be seen by the human eye. When white light strikes an object a portion of the spectrum is typically absorbed (the exceptions being white objects that reflect all visible wavelengths and black objects that absorb all visible wavelengths) with the non-absorbed portion of the spectrum reflected and perceptible by the human eye. For example,FIG.2Aprovides two exemplary illustrations200of white light201and204illuminating a red surface202and a green surface205, respectively. The red surface202is shown absorbing all of the visible light except red light203, which is reflected203and therefore detectable to the human eye. The green surface205behaves in a similar manner, and the green surface205absorbs all of the visible light except green light206, which is reflected206and detectable to the human eye.

However, all light sources do not necessarily embody the full visible white light spectrum. When portions of the visible light spectrum are missing from the light source, the quality of the light is defined in terms of a theoretical blackbody radiator heated to varying degrees on the Kelvin (K) temperature scale, with lower temperatures containing more red light and higher temperatures containing more blue light. For example, studio white lights typically emit light at 3,200° K, candle and sunrise or sunset light emissions are around 1,850° K, standard incandescent light is around 2,400° K, standard fluorescent lamp light is around 5,000° K, and an overcast daylight day is around 6,500° K. If portions of the visible light spectrum are missing from the light source, the amount and type of light reflected from an object will differ. For example, the two exemplary illustrations200ofFIG.2Adisplay the light sources201and204emitting white light (e.g., at 3,200° K). If the light sources201and204were instead emitting mostly red light (e.g., at 1,850° K), the red surface202would still appear red because red light203would still be reflected from it; but, the green surface205would appear black or dark gray because no green light206would be reflected, since green light was not present in the light source204.

Any reflected light that contacts a human eye is ultimately focused onto the light-sensitive retina at the back of the eye. The retina itself is comprised of tens of millions of photoreceptors that are either single photopigment “rods” (i.e., can “see” only varying degrees of gray in dim lighting conditions) or one of three types of “cones” where the three cone types differ in the photopigment they contain, this difference in photopigments enable a human's ability to see color. Each of these three photopigments has a different sensitivity to light of different wavelengths, and for this reason are referred to as “Blue,” “Green,” and “Red,” or, more appropriately, Short (S), Medium (M), and Long (L) wavelength cones, terms that more or less describe their spectral sensitivities.FIG.2Bprovides a graph220of the three types of cones “blue” or “S”223, “green” or “M”224, and “red” or “L”225of the wavelength of the visible light spectrum in nano meters (nm) charted on the horizontal axis222or abscissa and the cone's relative sensitivity to a particular wavelength charted on the vertical axis221or ordinate. As apparent from graph220, each of the three cone's sensitivity is an approximate Gaussian distribution with averages centered about three different wavelengths—i.e., “blue”223at 445 nm, “green”224at 535 nm, and “red”225at 575 nm. As is also apparent from graph220, there is significant overlap between the sensitivity Gaussian distributions of the three cones, particularly the “green”224and “red”225cones.

In addition to asymmetrical overlapping of cone sensitivity curves, the quantity of each type of cone present in the eye is not evenly proportioned. About 64% of the cones respond most strongly to red light, while about 34% respond mostly to green light. Only 2% of the cones respond strongest to blue light. Further, the lens and cornea of the eye tend to block shorter wavelengths, thereby further reducing sensitivity to blue and violet light.

Consequently, some colors are perceived by a human observer with greater luminescence intensity than other colors. Blue, green, and red colors are more intense (assuming the same number of photons are exciting the cones in each case) if the photon's excitation wavelength is near the Gaussian distribution centered averages—i.e., “blue”223at 445 nm, “green”224at 535 nm, and “red”225at 575 nm. Additionally, most colors are wavelengths of light that are received by more than one type of cone. For example, the color yellow is received by both the “green”224and “red”225cones that become highly excited since the yellow light wavelength (i.e., 570 to 580 nm) is near both cones' peak sensitivity. With the exception of the color white (all cones excited), the color yellow is the second highest level of excitation the human eye can experience. Thus, the color yellow appears to a human to be the brightest in the spectrum.

An approximation of the human eye's disproportionate sensitivity to the different visible color wavelengths is graphed230inFIG.2C. Similar to before, with graph230the wavelength of the visible light spectrum in nano meters (nm) is charted on the horizontal axis232or abscissa with a human's relative sensitivity to a particular wavelength or color charted on the vertical axis231or ordinate. As shown in graph230, the combined overlap between the “green”224and “red”225cones (FIG.2B), merged with the disproportioned quantity of each type of cone present in the eye, compounded with the eye's lens and cornea tendency to block shorter wavelengths (i.e., reducing sensitivity to blue and violet light) result in a Gaussian sensitivity distribution of the human perception of the color yellow235(FIG.2C) being observed as the most intense, with the standard color green234second intense, the standard color red236third intense, and the standard color blue233fourth intense. The reported “Most Visible Color in the World” (Ferro Shaunacy, 10thof May 2017, Mental Floss paper) is a shade of green237(i.e., 555 nm wavelength) that while not falling on top of curve230is near the top with the most visible status attributed to the combination of high luminescence intensity and contrast to typical environments. From this example, it can be seen that not all colors are weighed by the human eye on an equal basis. The differences in color perception and contrast with backgrounds providing significant consideration when determining what objects are typically legible to a human eye.

Reference will now be made in detail to example embodiments of the present disclosure, with one or more embodiments of illustrated in the drawings. Each example embodiment is provided by way of explanation of the present disclosure, and not meant as a limitation of the present disclosure. For example, features illustrated or described as part of one embodiment, may be used with another embodiment to yield still a further embodiment. The present disclosure encompasses these and other modifications and variations as come within the scope and spirit of the disclosure.

Various embodiments of the present disclosure relate to a redundantly printed security-enhanced document comprising a substrate and at least two different variable indicia printed with component colors directly or indirectly on the substrate such that the combined component color indicia create a composite process color variable indicum. The plurality of printed variable indicia are printed in the same general predefined area such that the printed variable indicia overlap or are registered so closely together such that a failure to print one or more portions of any one component color indicium does not alter the meaning of information represented (by the composite process color variable indicum) on the redundantly printed security-enhanced document. Each variable indicium is comprised of a component color that by itself displays sufficient luminescent intensity to remain legible to human eye photoreceptors. In various embodiments, redundancy is achieved via multiple ink applications with separate physically distinct print heads, as a function of the serial application of the individual component colors. In various embodiments, the at least first printed variable indicium and the at least second printed variable indicium are printed using different component colors that combine into the composite process color variable indicum.

In various embodiments, a portion of the composite process color variable indicum at least partially can comprise one or more numerals. Optionally, another portion of the at least composite process color variable indicum can partially comprise one or more words. A portion of the composite process color variable indicum at least can comprise one or more drawings, photographs, or other images.

In certain embodiments, the contrast between the luminescence intensity of the underlying substrate and the luminescence intensity of each component color of the at least two printed variable indicium are selected to ensure legibility of human eye photoreceptors, thereby ensuring the meaning of information represented by the resulting composite process color variable indicum in the event that the printing of one or more portions of either or any of the at least two printed component color variable indicium malfunctions. These embodiments thereby compensate for optical noise variances introduced by less-than-optimal underlying substrate discoloration and/or low contrast as perceived by the human eye.

In various embodiments, the composite process color variable indicia are each composed of at least two separate component colors. Thus, in these embodiments, imaging redundancy relative to human eye photoreceptors is better ensured since the different component colors require different ink applications with the different ink applications providing redundancy due to different application hardware, ink, etc. for each color.

Other objects and advantages of the present disclosure will be set forth in part in the following description, or may be apparent from the present description, or may be learned through practice of the present disclosure. Described below are a number of variable indicia determination process, printing mechanisms, and methodologies that provide practical details for reliably determining and producing redundant indicia under a SOC that are better immune to failure of any one high speed variable ink application system. Although the examples provided herein are primarily related to instant lottery tickets, it is clear that the same methods are applicable to any other type of document (e.g., telephone card, prepaid cards, vouchers, bank security instruments, coupons, etc.) such as where information is protected by a SOC.

As can now be appreciated in view of the previous summary of the present disclosure, in various embodiments printing indicia redundancy is achieved by employing at least two separate component colors to image a combined or composite process color variable indicum. Thus, so long as each component color is legible if printed individually, process color indicia printing redundancy is achieved and consequently the indicia non-defect rate is most probably increased to a percentage well beyond the Six Sigma (60) reliability standard cited in the background section of the present disclosure. While recent proposals teach how to achieve variable indicia redundancy by combining component color indicum embodiments into a composite process color indicium, the criteria for determining component color indicum legibility in such proposal has been primarily structured to accommodate machine garnered metrics and not necessarily optimized for viewing by the human eye. In contrast, while still utilizing machine garnered metrics, the present disclosure teaches how a system can optimize component color indicum legibility from a human eye perspective primarily by utilizing an additive color model instead of subtractive color models.

For example,FIG.3Adepicts a representative example of a modified known lottery-type instant ticket indicium300comprised of multiple (e.g., four—CMYK) ink applications overlaying the same image thereby producing a redundant composite process color indicium. To better illustrate the concept of multi-application printing, redundancy indicium300includes four simulated color misprints—327through330. The correctly printed portions326illustrate how the indicium would appear with no misprints. The misprints illustrated in indicium300are: (1) the right half of the “$” symbol327missing the cyan ink application, (2) the right half of the “5” numeral328missing the magenta ink application, (3) the tens place “0” numeral329completely missing the yellow ink application, and (4) the right half of the units place “0” numeral330missing the black ink application. As is readily apparent in the redundant variable indicium300ofFIG.3A, the absence of any one of the CMYK process colors still leaves indicium300easily readable in its intended form. Arguably, it is somewhat difficult for one not skilled in the art to detect any failure of ink applications in indicium300. Thus, the redundant printing of all of the CMYK colors alleviates any reasonable misinterpretation of the information conveyed by the variable indicium300, namely a value of “$5.00.”

However, this known process achieve redundancy with at least two component colors printed with minimum theoretical gray scale levels (e.g.,FIG.1F,130). While this methodology has the advantage of adding redundancy and consequently greatly reducing the printing error rate of indicia, it also has the disadvantage of possibly needlessly restricting the set of available redundant component colors (e.g., a 15% minimum gray scale threshold would result in zero redundant composite process colors comprised of two component colors where one of the two component colors was yellow, since an 100% application of yellow131only equates to a 12% grayscale132as shown inFIG.1F). Additionally, since the component colors are selected by their grayscale equivalency that is a function of the component color printing density and not necessarily how the resulting printed indicium is perceived by the human eye, some component colors that may pass the theoretical redundancy criteria may pose legibility challenges for some observers under some circumstances and vice versa.

Thus, while this known method uses process colors to incorporating redundancy into indicia imaging, this known method defines component colors that can be redundant as having a grayscale threshold value above a theoretical minimum only in a subtractive color model. In other words, the grayscale threshold values are a function of the component color printing density and substance in a subtractive color model and not how the resulting printed indicia is perceived by the human eye—typically depicted by an additive color model. Therefore, since the purpose of redundant composite process color indicia is to convey redundancy information to human eye photoreceptors, the use of a subtractive color system for determining component color redundancy has the disadvantages of being non-optimal as well as needlessly restricting relative to human perception.

The present disclosure contemplates that these disadvantages can be mitigated or eliminated by qualifying component colors for composite process color indicia redundancy relative to their perception to human eye photoreceptor cones—in part by utilizing an additive color model. The additive color model as disclosed in the present application to an extent mimics the human eye's photoreceptor perception, thus ensuring that each selected redundant composite process color indicium's component color will reliably convey the indicium's intended information when viewed solely or as part of the composite process color indicum.

The present disclosure recognizes that ensuring the redundancy and reliability of SOC protected indicia across tens of billions of printed documents in an economically viable fashion requires synchronized multiple imaging of indicia in register in the same general predefined area such as by using process colors. Thus, redundancy is achieved by determining and confirming that at least two component colors comprising a combined composite process color indicium each retain sufficient legibility to convey the intended information of the composite process color indicium in the event of a failure of at least one component color or a portion thereof. By employing off-the-shelf process color digital imagers or printers to image or print composite process color indicia with at least two separate component color physical print heads printing the same indicium, production efficiencies with very high reliabilities can be realized. So long as at least two separate component colors are printed by physically separate print heads with each component color legible when viewed individually and as part of a composite process color indicum, redundancy is achieved. Therefore, the present disclosure contemplates that this redundancy disclosure determines or selects component colors that are readily observable to human eye photoreceptor cones when viewed individually and are portions of an overall redundant composite process color indicium. The human eye perspective is achieved by utilizing an additive color model that enables ready selection of qualifying redundant component colors used to create composite process color indicia.

With various additive color model emulating human eye photoreceptor perception it is necessary to establish the color temperature of the light illuminating the process color indicia. As previously described, the two exemplary illustrations200ofFIG.2Aassume the light sources201and204are emitting white light (e.g., at 3,200° K). If the light sources201and204were instead emitting mostly red light (e.g., at 1,850° K) the red surface202would still appear red because red light203would still be reflected from it; however, the green surface205would appear black or dark gray because little or no green light206would be reflected, since green light was not present in the light source204. In other words, since the perceived color of an indicium is a function of the illuminating light source, the perceived color will vary depending on the color temperature of the light—e.g., in the previous example, a red indicium would still appear red, but a green indicium might appear black under the same illumination. While there are a large quantity of possible color temperatures for illuminating light that can realistically occur when humans are viewing printed process color indicia (e.g., candle light, low bar lighting, fluorescence light, sunlight), it is impractical to attempt to model all possible illuminating light color temperatures; thus, when qualifying the redundancy of component color indicia, it is advantageous to assume the indicia will be observed in studio quality white light—i.e., 3,200° K. The 3,200° K color temperature displaying the “true” or (more to the point) the intended color of the indicia and arguably being the color temperature of the illuminating light that would be used to verify any apparent winning tickets or documents. The commercial standard Adobe Photoshop RGB, 8-bit color profile (effectively replicating 3,200° K illumination) is one profile additive color model embodiment for the present disclosure. Other profiles (e.g., Apple RGB) can under some circumstances be more desirable to employ.

Thus, by analyzing each component color's qualification for legibility and consequently redundancy with reference to an additive color model (i.e., RGB) emulating human eye photoreceptors under a given quality of illumination (e.g., 3,200° K) instead of the component color's qualification for legibility and redundancy utilizing a subtractive color model (i.e., CMYK) in grey scale, the systems and methods of the present disclosure provide significant gains in the scope and quality of component color selection can be realized. While the selection of an additive color model for determining indicia component color redundancy may seem counterintuitive, composite process colors are typically comprised of at least the primary subtractive colors Cyan, Magenta, and Yellow (CMY)—i.e., the same colors that define subtractive color models. In other words, when formulating any composite process color, a subtractive color model must be employed. Though, while this is true for composite process color formulation, when attempting to determine the legibility of any component color or resulting process color to the human eye it is necessary to consider the transmitted wavelengths of light rather than the pigments themselves, therefore measuring component colors and/or composite process colors with an additive color model at a standard theoretical color temperature.

While there are numerous commercial off-the-shelf additive color models available (e.g., Apple RGB; Adobe RGB; Digital Camera Initiative Publication 3 or “DCI-P3”; Standard RGB or “sRGB”), the standard Adobe RGB model operating in 8-bit can be employed for performing part of the analysis of component and composite process color redundancy. The Adobe RGB model provides universal applicability to most if not all computing and printing platforms as well as its seamless integration with Adobe Photoshop 5 CMYK subtractive color model, which is the generally accepted subtractive model for process colors in the printing industry.

By evaluating each component and composite process color with the Adobe RGB (8-bit) additive model, each candidate color can be viewed in red, green, and blue channels separately; thereby, enabling color metrics and associated analysis that more closely model the red, green, and blue photoreceptor cones of the human eye—seeFIG.2B. For example,FIG.5Aprovides a front elevation view of a known representative example of a 10×10 matrix500of one hundred process color cells with each color comprised of at least one component of CMYK. This same matrix500is shown in theFIG.5Billustration510; however,510ofFIG.5Balso illustrates the same matrix as it would be approximately observed by human eye red516, green517, and blue518cone photoreceptors rows—i.e., with human color photoreception, the three RGB cone inputs225,224, and223(FIG.2B) are transmitted to and combined in the brain to produce our standard color perception515(FIG.5B).

Thus, by the system and method analyzing component and composite process colors with an additive (i.e., RGB) color model, greater understanding can be realized of how a color is perceived by a human and more to the point how likely a particular color is to appear legible to a human when utilized for variable indicia redundancy. Nevertheless, it should be noted that while standard RGB additive color models (e.g., Adobe RGB) accurately reflect the red, green, and blue reflected light components of a particular color with a given color temperature illumination, these same additive models do not typically emulate the biasing that the human eye inherently has when perceiving RGB light. This is because standard RGB additive color models are configured to emulate the reflected light emitted from a real world object under a given color temperature illumination such that a computer monitor, television, or movie screen can accurately reproduce the same type of light for human perception. However, this is not the same as an additive color model seeking to emulate human color perception. While this difference between “emission” and “perception” may appear to be trivial or confusing, it is important when establishing a standard for machine metric indicia component and composite process color redundancy that is derived independent of a “qualified” human simply looking at a given color and determining whether or not it is acceptable for indicia redundancy.

As previously explained, human eye photoreceptors are divided into three different types of color sensitive cones—i.e., long wavelength “red” cones, medium wavelength “green” cones, and short wavelength “blue” cones (see225,224, and223ofFIG.2B). As apparent from graph220, each of the three cone's sensitivity is an approximate Gaussian distribution with averages centered about three different wavelengths with significant overlap, particularly the “green”224and “red”225cones. In addition to asymmetrical overlapping of cone sensitivity curves, the quantity of each type of cone present in the eye is unevenly balanced. About 64% of the cones respond most strongly to red light, while about 34% respond mostly to green light with only 2% of the cones responding strongest to blue light. Additionally, the lens and cornea of the eye tend to block shorter wavelengths, thereby further reducing sensitivity to blue and violet light. Accordingly, some colors are perceived by a human observer with greater luminescence intensity than other colors. Blue, green, and red colors are more intense (assuming the same number of photons are exciting the cones in each case) if the photons' excitation wavelength are near the Gaussian distribution centered averages—i.e., “blue”223at 445 nm, “green”224at 535 nm, and “red”225at 575 nm. Additionally, most colors are wavelengths of light that are received by more than one type of cone with the color yellow received by both the “green”224and “red”225cones since yellow light wavelength (i.e., 570 to 580 nm) is near both cones' peak sensitivity resulting in the color yellow as the second highest level of excitation the human eye can experience (white being the highest).

When taking these color asymmetries into consideration, an approximation of the human eye's disproportionate sensitivity to the different visible color wavelengths is provided in graph230ofFIG.2C. With graph230, the combined overlap between the “green”224and “red”225cones (FIG.2B), combined with the disproportioned quantity of each type of cone present in the eye, also shared with the eye's lens and cornea tending to block shorter wavelengths results in a Gaussian sensitivity distribution of the human perception with the color yellow235(FIG.2C) being observed as the most intense, then the color green234second intense, the standard color red236third intense, and the standard color blue233fourth intense. This type of asymmetrical color luminescence intensity modeling is typically not conveyed in the standard “emission” additive color models commercially available, because the design goal with these types of models is to accurately project light to the human eye, not convey how those projected colors are perceived by a human within a machine's memory.

As before, this distinction between standard “emission” additive color models commercially available and the internal “perception” of a human to color may seem trivial or may appear to be confusing, but if the goal is to qualify component or composite process colors for indicia redundancy using defined metrics and processes, it is desirable for the additive color model employed to be tuned such that it more closely resembles human “perception” than the “emission” of light reaching a human's eye. By selectively limiting the range of some RGB channels from the lower (i.e., darker) portion of the selectively limited channel color's gamut, an additive color model can be derived that reasonably emulates human color perception. Thus, with this selective tuning an additive color model more closely resembling human “perception” can be employed to automatically and consistently analyze candidate redundant component and composite process colors for redundancy suitability independent of human operator input.

More specifically, for example, in one embodiment of the present disclosure the Adobe RGB (8-bit) additive color model channels are selectively tuned such that the green channel remains unaltered, the red channel's lower (darker) end gamut is reduced by 3%, and the blue channel's lower (darker) end gamut is reduced by 7%. In an alternative embodiment, the standard relative luminance conversion by multiplying: the red channel output by the coefficient “0.2126”, the green channel output by the coefficient “0.7152”, and the blue channel output by the coefficient “0.0722”. Other embodiments of the present disclosure contemplate emulating the human eye's color perception gamut where green light contributes the most to the intensity perceived by humans and blue the least are possible.

Whichever tuning model is employed, this selective channel tuning of the additive color model simulates human visual perception by: mimicking the wavelengths of light received by each of the three types of cone photoreceptor in the human eye, allowing for the percentage of each type of cone present in the human eye, simulating the proportioned overlap between each type of cone's optical bandwidth, etc. any suitable selective tuned additive color model developed for indicia redundancy results should at least initially be reviewed and audited to confirm that the model is in fact accurately reflecting human color “perception”—the goal being to provide a reliable, repeatable, and auditable additive color model that can be universally employed to ensure indicia redundancy. There are other methods of tuning existing RGB additive color models that can be employed under some circumstances. For example, a given pixel's luminescence intensity values from at least two different channels (e.g., red and green) can be summed and transposed into a new fourth (summation) channel that can be weighed against standard RGB values, individual color channel gamut range can be reduced by deletion of Least Significant Bits (LSB), etc.

Regardless of the additive RGB color model utilized to simulate human color perception, once a given component or composite process color has been broken down by the chosen additive color model to its discrete digital RGB channel values, further processing is required to provide a metric for determining whether the given component or composite process color is acceptable for redundant indicia utilization. In certain embodiments, each RGB model channel is converted to its grayscale equivalent in which the value of each pixel is a single sample carrying only luminescence intensity information with the sum of all pixels contained in the color sample image's field of view comprising the data that is evaluated for each channel. Assuming the field of view exclusively contains a homogeneous distribution of only the component or composite process color being evaluated, a relative analytic can be determined that can effectively provide a minimum threshold of legibility of each component or composite process color's suitability for indicia redundancy. With these particular embodiments, the grayscale equivalent values of all the pixels in the field of view are mean averaged with the resulting metric compared to a theoretical minimum threshold value (e.g., ≥15%) where if the mean averaged metric is less than the theoritical minimum threshold value the tested color is deemed insufficient for redundancy, and conversely if the mean averaged metric is greater than or equal to the theoretical minimum threshold value then the tested color is deemed to be acceptable for use with indicia redundancy. There are other methods for determining a relative analytic metric qualification for indicia redundancy (e.g., modal average, median average, Kalman filter for noisy images prior to averaging) that may under some circumstances be more desirable in accordance with the present disclosure.

While there are multiple methods to provide a metric for gray scale equivalence, when determining a relative analytic metric qualification for indicia redundancy for a component or composite color's contribution to a redundant composite indicium process color, the printing convention of employing percentages (i.e., a scale of 0% to 100% line screen) can be employed. While the percentage range of this methodology encompasses a total of only one hundred and one intensities, the range is nevertheless sufficient to reliably identify thresholds for minimum legibility of each contribution component color for most circumstances. Also, the intuitive nature of percentile notation is commonly used in printing to denote how much ink is employed in halftoning and is thereby a familiar standard for most printers. It should also be noted that the common printing percentile notation approach scale is reversed to most other systems of grayscale measurement, in that a value of 0% denotes white and a value of 100% total black (saturation). There are other methods of grayscale numerical representation (e.g., rational numbers, binary quantized values) that may be more desirable in some circumstances in accordance with the present disclosure.

Various embodiments include printing percentile notation to determine minimum thresholds of redundancy, to ensure redundancy, two or more component colors can be combined in such a way that should a portion of any component color fail to print the remaining color(s) need to contribute or combine to exhibit a minimum of 15% (for a white substrate background) or 25% (for a dull or colored substrate background) grayscale equivalent over the entire process color indicium when viewed in at least one of the additive color channels (i.e., red, green, or blue). These theoretical threshold values should be viewed as extremely conservative to ensure variable indicia legibility under non-optimal conditions (e.g., low lighting, direct sunlight, poor printing substrate). Different theoretical threshold values are possible and desirable under different circumstances—e.g., 11% (typical white background, typical lighting) or 18% (typical dull or colored background, typical lighting) grayscale equivalent.

Finally, the pass (logic “1”) or fail (logic “0”) results from the theoretical threshold tests for each of the three channels (i.e., RGB), are logic inclusive-OR together resulting in any one or more of the RGB color channels passing the theoretical threshold tests qualifying the component or composite process color as redundant. The logic inclusive-OR of any passing test result effectively emulating the human eye's perception, since indicium legibility with any one type of color cone photoreceptor would mean the indicium would be legible to a human.

In the above disclosure, it should be appreciated that variable indicia theoretical threshold values vary depending on the background behind the variable indicia. This is because human visual perception is more sensitive to contrast than absolute luminance—e.g., humans can perceive the world similarly regardless of the huge changes in illumination over a day or from place to place. With human visual perception, contrast is determined by the difference in the color and brightness of the object and other objects within the same field of view. When determining metrics for variable indicia component or composite color redundancy, the significance contrast is the contrast ratio between the printed variable indicia and its associated background.

For example,FIG.3Bprovides two images (350and350′) of the same lottery-style SOC secured instant ticket differing only with low contrast350and high contrast350′ backgrounds in the general area of the variable indicia (351and351′). Low contrast image350is illustrated with a plurality of printed variable indicia351printed on top of a dark or gray background (352,353, and354). Most traditional lottery-style SOC secured instant tickets feature this type of low contrast background (352,353, and354) since the tickets are printed on paper with lower security ink films layers printed under the variable indicia typically exhibiting a low contrast background due to an opacity ink film layer comprised predominately of carbon—i.e., it is difficult to print a smooth high contrast covering ink film layer over a carbon black ink film layer. Recently, various technology advancements have enabled variable indicia imaging on a high contrast (e.g., white) background. Additionally, known lottery-style SOC secured instant tickets using a foil substrate also provide a high contrast background for variable indicia. Whichever technology is employed, high contrast lottery-style SOC secured instant tickets similar to image350′ are possible with variable indicia351′ printed on high contrast smooth backgrounds (352′,353′, and354′). In the example images350and350′ ofFIG.3B, the black monochromatic variable indicia (351and351′) is clearly legible on both tickets, however it is nevertheless also readily apparent that with the higher contrast background352′,353′, and354′ the variable indicia351′ appears sharper and more well defined. When process colors are employed to image variable indicia this sharper and more defined difference is even more pronounced.

Accordingly, variable indicia theoretical threshold values can vary depending on the background behind the variable indicia in accordance with the present disclosure. The goal being to ensure that a sufficient Signal-to-Noise ratio (“S/N”) is maintained between the variable indicia intended information (signal) and the background behind the variable indicia (noise). For determining a variable indicia signal to background noise “Si/Nb”, one possible method would be to directly apply “Weber's Fraction” (known in the art as a means of determining visual contrast where small features are present on a large uniform background) as described by the following equation:

Si/Nb=I-IbIbWhere: I=the luminescence of the variable indiciaIb=the luminescence of the background

However, there are several problems with directly adapting “Weber's Fraction” to an additive RGB color model for determining human legibility of indicium relative to background substrate noise. First, “Weber's Fraction” is intended to determine contrast for units of luminescence, not in the preferred units of 0% to 100% line screen gray scale. Secondly, a direct application of “Weber's Fraction” would essentially compare a single pixel on the indicium to a single pixel in the background, while this would be acceptable with homogeneous color indicium and backgrounds it would not provide acceptable metrics for heterogeneous indicia and/or backgrounds.

For example,FIG.3Cillustrates five different variable indicia (380/381′/381″ thru384/384′/384″) imaged on three different backgrounds (375thru377). As is apparent inFIG.3C, the three different types of backgrounds are arranged as rows with row375displaying an exemplary homogeneous high contrast white background, row376displaying an exemplary homogeneous low contrast gray background, and row377displaying an exemplary heterogeneous variable background. The five different exemplary types of variable indicia are arranged in columns with column indicated by380,380′, and380″ displaying a color homogeneous indicium, column indicated by381,381′, and381″ displaying a slightly (i.e., black boarder) heterogeneous indicium, and the other three columns respectively indicated by382thru382″,383thru383″, and384thru384″ displaying varying degrees of heterogeneous indicium. Thus, in the example ofFIG.3C, “Weber's Fraction” would only yield theoretical usable Si/Nbresults for indicium380and380′ on background rows375and376—i.e., all other indicium would potentially yield erroneous results as would background row377.

Though, by modifying “Weber's Fraction” equation to allow for variances in both the variable indicium and associated background, usable Si/Nbresults may be obtained. This “Modified Weber's Fraction” equation produces usable Si/Nbresults for both homogeneous and heterogeneous variable indicium as well as associated background using the percentage units of 0% to 100% line screen gray scale is provided below:

Si/Nb=μi(μb+σb)(μb+σb)Where: μi=is the mean average of the variable indicium in units of modified gray scaleμb=is the mean average of the background in units of modified gray scaleσb=one standard deviation of the background in units of modified gray scale
In the above Modified Weber's Fraction equation variable definition the term “in units of modified gray scale” repeatedly appears. In the context of this disclosure, the term “modified gray scale” means that the standard gray scale of 0% to 100% line screen is concatenated to effectively eliminate 0%—i.e., 0% thru 1% are equated to 1% for the purpose of this preferred Modified Weber's Fraction Si/Nbequation. This modification was necessary to eliminate the possibility of dividing by zero (i.e., perfectly white substrate) in the Modified Weber's Fraction Si/Nbequation at the cost of losing approximately 0.99% fidelity. It should be also noted, that the reason for the asymmetry in the numerator of the Modified Weber's Fraction Si/Nbequation (i.e., the variable indicium value is only derived from its mean average “μi” in gray scale, whereas the background value is derived from the sum of its gray scale mean average “μb” and one standard deviation “σb”) is because the variable indicium is typically evaluated with each of its component colors separately, thereby normally resulting in less variance, while some backgrounds can vary significantly (e.g., rows376and377ofFIG.3C) with the added one standard deviation accounting for this variance in backgrounds. This is true, even though variable indicium component colors may vary in line screen over the same component color application (e.g., variable indicium383); however, it has been found that any variable indicium line screen variance of a component color does not significantly deviate from its mean average.

However, there remains the special case of the variable indicia being defined by the absence of imager ink where the actual indicium is created by “knocking out” (removing ink from an area) a portion of a continuous imaged background in the shape of the desired variable indicium—e.g., the continuous imaged background390and knocked out variable indicia ofFIG.3D. The Si/Nbfor this special case may still be calculated using the Modified Weber's Fraction Si/Nbequation by simply reversing the variable indicia and background variables—e.g., the printed portion of the variable indicia391ofFIG.3Dwould assume the variables “μb” and “σb” with the continuous imaged background390assuming the variable “μi” in the Modified Weber's Fraction Si/Nbequation.

Thus, the above disclosure of the Modified Weber's Fraction Si/Nbequation enables a metric to be calculated from applying grayscale measurements of a variable indicium and associated background to determine the signal-to-noise level existing between the variable indicium and the background. However, the Modified Weber's Fraction Si/Nbequation does not specify the minimum acceptable Si/Nbvalue required to ensure legibility of a given variable indicium component color over a given background. Once the Modified Weber's Fraction Si/Nbequation's results are applied to a variety of variable indicium component colors and associated backgrounds, it appears that a Si/Nbof at least “3.7” would produce reliable legible indicium. While this is less than the generally accepted “Rose criterion” level of a minimum S/N of “5” needed to be able to distinguish image features with certainty, the reduced legibility threshold for the Modified Weber's Fraction Si/Nbequation can be attributed to different criteria measured (“Rose criterion” typically utilizes lumens), a reduced scale of one hundred possible levels, and clearer demarcation between variable indicia and associated background.

FIGS.4A,4B, and4Cillustrate different embodiments of the previously explained additive model luminescence intensity testing for certain indicia redundancy embodiments as multichannel flow charts400,450, and470in accordance with the present disclosure. As illustrated in the multichannel flowcharts400and470, these example embodiments of the present disclosure are conceptually divided into four groups (i.e., “Non-Additive Model Processing”401and471, “Additive Model Red Channel”401R and471R, “Additive Model Green Channel”401G and471G, and “Additive Model Blue Channel”401B and471B) by the four “multichannel” columns as shown inFIGS.4A and4C. For these example embodiments, a particular flowchart function appears completely within a channel, its functionality is limited to the data category of the associated channel. For example, Red Grayscale404R is exclusively processed in the Additive Model Red Channel column401R. It should be appreciated that these functions shown in these flowcharts and described below would be performed by various embodiments of the systems of the present disclosure.

TheFIG.4Amultichannel flowchart400begins with the candidate component or composite process indicia color402submitted in a digitally suitable image format with its field of view comprised (at least primarily) of the candidate indicia color402. Optionally, if the candidate indicia color402is a composite process color, its additive primary component colors (e.g., cyan, magenta, yellow, and/or black) should each be tested individually for indicia redundancy.

This candidate indicium color402image is then broken down by the chosen additive model into red403R, green403G, and blue403B segments with each segment emulating the luminescent intensity as perceived by the human eye “red”, “green”, and “blue” cone photoreceptors respectively. Once the complete “white light” or “full color” image402has been broken down into its red403R, green403G, and blue403B segments, each segment is then converted to grayscale404R,404G, and404B such that value of each grayscale pixel conveys a metric representing the intensity of that pixel for its respective color channel. Next, the intensity values of all the pixels in the field of view are averaged for each color channel or segment (405R,405G, and405B) thereby providing a single averaged metric for each discrete color channel. At this point, optional biases can be applied to any or all of the three color channels' derived metrics (406R,406G, and406B), thereby “tuning” the additive color model to more accurately reflect the perception of human eye photoreceptor cones.

The next step is to perform a threshold test (407R,407G, and407B) on each of the three derived color channel metrics, where each metric is compared to a theoretical threshold value (i.e., greater than or equal to X) to determine a pass (logic “12”) or fail (logic “02”) test result of the candidate color for indicium redundancy, relative to each color channel. The three binary indicium redundancy test results (407R,407G, and407B) are then Boolean logic inclusive-OR together408with any one single resulting passing output bit determining if the candidate color is suitable for indicia redundancy409.

In an alternative embodiment indicated by numeral470ofFIG.4C, optional biases can be applied in alternately or addition, after the segmentation (473R,473G, and473B) process, thereby employing the “tuning” process with a larger set of data (e.g., 8-, 16-, 24-, 30-, 36-, or 48-bit color). In the alternative embodiment indicated by numeral470, the process logic flow is similar to what has already been disclosed inFIG.4Astarting with the candidate component or composite process indicia color472(FIG.4C) submitted in a digitally suitable image format with its field of view comprised mainly of the candidate indicium composite or component color472.

As before, this candidate indicium color472image is then broken down by the chosen additive model into red473R, green473G, and blue473B segments with each segment emulating the luminescent intensity as perceived by the human eye “red”, “green”, and “blue” cone photoreceptors respectively. Once the complete “white light” or “full color” image472has been broken down into its red473R, green473G, and blue473B segments, optional biases can be applied (e.g., multiplying the red channel's intensities by the coefficient “0.2126”, multiplying the green channel's intensities by the coefficient “0.7152”, and multiplying the blue channel's intensities by the coefficient “0.0722” as previously discussed) to any or all of the three color channels' derived metrics (474R,474G, and474B), thereby “tuning” the additive color model to more accurately reflect the perception of human eye photoreceptor cones. At this point, each segment is then converted to grayscale475R,754G, and475B such that value of each grayscale pixel conveys a metric representing the intensity of that pixel for its respective color channel. Next, the gray scale intensity values of all the pixels in the field of view are averaged for each color channel or segment (476R,476G, and476B) thereby providing a single averaged metric for each discrete color channel.

The next step is to perform a threshold test (477R,477G, and477B) on each of the three derived color channel metrics, where each metric is compared to an i theoretical threshold value (i.e., greater than or equal to X) to determine a pass (logic “1”) or fail (logic “0”) test result of the candidate color for indicia redundancy, relative to each color channel. The three binary indicia redundancy test results (477R,477G, and477B) are then Boolean logic inclusive-OR together478with any one resulting passing output bit determining if the candidate color is suitable for indicium redundancy479.

In addition to luminescence intensity testing to determine a candidate component or composite process color's qualification for indicia redundancy, the contrast between a candidate component or composite process color and its background or nearby surroundings can also be used as a metric to qualify component or composite process colors for indicia redundancy. Dr. Simon Laughlin's 1981 seminal paper “A simple coding procedure enhances a neuron's information capacity” (Department of Neurobiology, Research School of Biological Sciences, P. O. Box 475, Canberra City, A. C. T. 2601, Australia) demonstrates that all organisms with eyes are more interested in differences in luminescence, or contrast, than in luminescence per se. For this reason, the neurons which receive outputs from photoreceptors tend to respond to contrast rather than luminescence.

Thus, the previously disclosed luminescence intensity testing embodiment can be further expanded to provide an empirical contrast metric for indicia redundancy between candidate component or composite process colors and their background or surrounding area colors. With this specific contrast embodiment, the same processes for measuring grayscale with an additive RGB color model can be utilized to provide contrast metrics for the candidate component or composite process color relative to its background or surrounding area color(s). In this example contrast embodiment, the candidate indicium color and the background color(s) are compared in their grayscale equivalencies relative to each additive color model channel (i.e., red, green, and blue) with the grayscale ratio or delta between the two utilized as the qualifying metric for determining indicium redundancy. This tends to ensure that the measured contrast ratio or delta value is greater than or equal to the theoretical contrast minimum threshold.

For example, assume a candidate component or composite process indicium color displays a grayscale equivalent value in the red channel of 13% with the associated background color(s) displaying a grayscale equivalent value of 3% in its red channel. If the theoretical contrast delta minimum threshold was ≥10%, the candidate component or composite process indicia color would qualify as redundant for indicia printing even if the indicia color luminescence intensity threshold was ≥15%—assuming that the candidate component or composite process indicia color was printed with the tested background color.

In an alternative embodiment, a contrast ratio methodology based on the Modified Weber's Fraction Si/Nbequation is employed as an empirical contrast metric for indicia redundancy between candidate component or composite process colors and their background or surrounding area color(s). With this alternative Modified Weber's Fraction Si/Nbequation contrast embodiment, the grayscale value of the indicium component or composite process color and the background or surrounding color(s) is determined per RGB channel as in the previous example contrast delta embodiment, but with the Modified Weber's Fraction Si/Nbequation contrast ratio embodiment, the resulting grayscale ratio effectively provides a comparison of the level of a desired signal (indicum color) to the level of background noise (background or surrounding color). A Si/Nbvalue greater than “1” indicates more signal than noise and equates to a theoretically legible indicia redundant component or composite process color when printed with the associated background color(s). However, as a practical matter, the minimum acceptable theoretical contrast Si/Nbvalue to ensure redundant indicia legibility should be sufficiently large to ensure redundant indicia legibility under most circumstances, including non-optimal environmental settings that may contribute additional noise such as bar lighting. An optimal minimum Si/Nbvalue is somewhat debatable, but a conservative minimum theoretical Si/Nbvalue for maintaining indicia redundancy would be a ratio of “3.7”. As before, the Si/Nbvalue would first be determined discretely relative to each of the three (i.e., RGB) additive model color channels, with each channel's pass (logic “1”) or fail (logic “0”) redundancy test logic inclusive-OR together resulting in the overall pass or fail redundancy status for that particular indicia and background color(s) combination. In other words, any one or more of the RGB color channels passing the theoretical contrast ratio tests qualifying the component or composite process color as redundant when printed with the corresponding background. The present disclosure contemplates that other methods of determining a contrast metric (e.g., first summing the results from the RGB channels for the indicium and the background and then determining the Si/Nbvalue) under some circumstances can be more desirable.

FIG.4Billustrates the previously disclosed additive model contrast testing for indicia redundancy against a known background embodiment as a multichannel flow chart450. As illustrated in the multichannel flowchart450, this embodiment of the disclosure is conceptually divided into four groups (i.e., “Non-Additive Model Processing”451, “Additive Model Red Channel”451R, “Additive Model Green Channel”451G, and “Additive Model Blue Channel”451B) by the four “multichannel” columns as shown inFIG.4B.

TheFIG.4Bmultichannel flowchart450begins with the candidate component or composite indicia color and the associated background color(s)452submitted in digitally suitable image formats with two field of views comprised of the candidate indicium color and the associated background color(s)452. The candidate indicium color and the associated background color(s)452images are each broken down by the chosen additive model into separate red453R, green453G, and blue453B segments with each segment emulating the luminescent intensity as perceived by the human eye “Red”, “Green”, and “Blue” cone photoreceptors respectively—inFIG.4Bthe parallel paths of the indicium and background color(s) processing are indicated by pairs of functional rectangles with one rectangle slightly offset and behind the other. Once the complete “white light” or “full color” images452have been broken down into red453R, green453G, and blue453B segments, all segments are then converted to grayscale454R,454G, and454B. Next, the intensity values of all the pixels in the field of view are averaged for each color channel or segment (455R,455G, and455B) thereby providing a single averaged metric for each discrete color channel. At this point, the candidate color is processed by the Modified Weber's Fraction with the associate background color(s) to derive a Si/Nbmetric (456R,456G, and456B) for each of the three color channels. Then, the three derived Si/Nbmetrics are compared to i theoretical threshold values to determine pass (logic “1”) or fail (logic “0”) test results of the candidate color and associated background color(s) for indicia redundancy (457R,457G, and457B). The three binary indicia redundancy test results (457R,457G, and457B) are then Boolean logic inclusive-OR together458with the single resulting output bit determining if the candidate color is suitable for indicia redundancy459when printed with its associated background color(s).

As in the previous embodiment, optional biases can be applied to any or all of the three color channels' derived metrics, thereby “tuning” the additive color model to more accurately reflect the perception of human eye photoreceptor cones. These optional biases can be applied after the segmentation (453R,453G, and453B) or grayscale conversions (454R,454G, and454B) processes, and/or after a Si/Nbvalue has been derived for each color channel.

The remainder of this specification will focus on the practical implications of these disclosures. Examples of redundant indicia colors as enabled by these disclosures are provided as well as an example of a redundant indicium that was not possible with known disclosures.

FIG.5Aprovides a front elevation view of a known representative example of a 10×10 matrix500of one hundred process color cells with each color comprised of at least one component of CMYK. As shown inFIG.5A, the matrix500is arranged in alphabetically assigned rows501(“A” through “J”) by numerical columns502(“1” through “10”) with each cell in the matrix500illustrating a different process color. The line screen percentage of each CMYK component color necessary to generate the process color of a given cell is provided in Table 1.

FIG.5Billustrates a copy of the representative color matrix500′ ofFIG.5Ain sixteen different multiple renderings arranged in a 4×4 grid510. The sixteen different renderings of grid510are arranged into four rows (515thru518) by four columns (511thru514). The first row515renders its matrices in white light illumination that is considered normal color perception. The second row516renders its matrices as perceived by human eye “red” cone photoreceptors. The third row517renders its matrices as perceived by human eye “green” cone photoreceptors. Finally, the fourth row518renders its matrices as perceived by human eye “blue” cone photoreceptors. The four columns (511thru514) vary by how the matrices' colors are displayed, with the first column511rendering the matrices in color with the second512, third513, and fourth514columns rendering the matrices in grayscale. Column512renders the matrices of column511in grayscale equivalent, thus providing graphic renditions of the relative luminescence intensities of each color in the matrix as perceived: normally (column512, row515), by red cone photoreceptors (column512, row516), by green cone photoreceptors (column512, row517), and by blue cone photoreceptors (column512, row518).

TABLE 1FIG. 5A Known Component Color BreakdownRowColor12345678910AC0%0%0%0%0%40%40%20%20%20%M0%0%0%0%0%0%0%0%0%0%Y0%0%0%0%0%0%0%0%0%0%K100%90%80%70%60%0%0%20%60%80%BC0%0%0%0%0%40%60%40%60%60%M0%0%0%0%0%0%0%0%0%0%Y0%0%0%0%0%0%0%20%40%60%K50%40%30%20%10%60%40%20%20%20%CC0%0%0%0%0%40%60%40%60%60%M0%0%0%0%0%0%0%0%0%0%Y0%0%0%0%0%0%0%20%40%60%K50%40%30%20%10%60%40%20%20%20%DC0%0%20%0%0%20%20%20%20%40%M100%100%80%60%40%0%0%0%0%0%Y100%0%0%100%20%20%40%60%40%100%K0%0%20%0%0%40%40%20%20%0%EC0%20%40%60%60%20%0%0%0%0%M20%20%40%40%60%0%0%0%0%0%Y20%0%0%0%0%60%20%20%20%40%K60%0%0%0%0%0%80%60%40%40%FC40%60%40%40%100%0%0%0%0%0%M40%40%40%20%20%0%0%0%0%20%Y0%0%0%0%0%60%60%40%20%40%K20%40%60%40%0%20%0%0%0%40%GC0%0%0%0%0%0%0%0%0%0%M40%20%60%40%40%40%60%40%40%20%Y60%60%80%80%60%0%0%0%0%0%K20%20%0%0%0%60%40%0%20%40%HC0%0%0%0%0%0%20%20%20%20%M20%20%20%60%60%20%60%80%60%40%Y100%40%40%60%80%0%0%0%0%0%K0%0%60%40%20%20%20%0%0%20%IC0%0%0%0%0%20%20%20%40%40%M60%40%20%40%60%40%0%40%60%100%Y60%40%20%20%40%0%0%0%0%0%K0%0%0%40%20%0%60%40%0%0%JC0%0%0%0%0%40%60%40%60%100%M60%100%60%80%40%80%80%60%80%100%Y20%60%40%40%20%0%0%0%0%100%K20%0%0%0%20%20%0%40%20%100%

In row515and columns512thru514, matrix color cells that are inherently non-redundant (i.e., printed with only one inkjet head—either only one cyan head, only one magenta head, only one yellow head, or only one black head) are highlighted519with a blue cell containing the null set symbol (i.e., “Ø”). It should be noted, that one additional cell in matrix location C1is also highlighted as non-redundant since it is white and is a special case simply showing the background substrate with no printing. In other words, since these highlighted process colors are printed with at most one print head and consequently at most one color, by definition these process colors are not redundant and therefore are flagged (“Ø”) and removed from further consideration.

Columns513and514provide the same grayscale intensity renderings as column512, but columns513and514also apply theoretical minimum grayscale threshold tests (i.e., 15% minimum threshold test for column513and a 25% minimum threshold test for column514) to the grayscale matrices of rows:516(red intensity tests),517(green intensity tests), and518(blue intensity tests). Any matrix color cell failing the respective intensity test (i.e., ≤15% minimum threshold for column513and ≤25% for column514) for rows516thru518is highlighted as a yellow cell520. All matrix color cells that failed an intensity test in rows516(insufficient red intensity),517(insufficient green intensity), and518(insufficient blue intensity), are logically ANDed such that any color cell that failed its intensity test for all three rows (i.e., insufficient RGB intensity) is deemed to be non-redundant and is highlighted521in row515columns513and514as a red cell containing the null set symbol (“Ø”). Thus, all remaining colors not covered by a colored cell with a null set symbol (“Ø”) in row515columns513and514matrices would be considered redundant in this example510.

For clarity, it should be noted that example510ofFIG.5Bdisqualified a particular color cell in its matrix only when the same color cell failed the threshold test for all three color channels (RGB)—i.e., logic AND of three separate threshold failures. This is identical to the disclosure examples ofFIGS.4Athru4C (400,450, and470respectively) where the outputs of the three threshold tests (407R,407G, and407B forFIG.4A; or457R,457G, and457B forFIG.4B; or477R,477G, and477B forFIG.4C) are logic ORed together (408FIG.4A,458FIG.4B, and478ofFIG.4C). The difference is in the example510ofFIG.5Bthe failures are logic ANDed and in the examples400,450, and470ofFIGS.4A,4B and4Cthe successes are logic ORed—i.e., the same outcome.

While example510ofFIG.5Bdoes demonstrate the essential concepts of the disclosure as well as disqualifying the matrix500′ color cells that are inherently non-redundant (i.e., process colors produced with at most one print head) as well as some composite process colors that lack the intensity to be employed to print redundant indicia (e.g.,521), it only evaluates process colors as printed with no regard to the component colors that make up the resulting composite process colors. For example, matrix500color cell “A7” or “Light Blue Green” (seeFIG.5A) is comprised of 20% cyan, 0% magenta, 0% yellow, and 20% black component colors. Most likely, either 20% cyan by itself would fall below the 15% theoretical intensity threshold and would definitely fall below the 25% theoretical intensity threshold, thereby making the color unsuitable for redundant indicia printing, since cyan by itself would exhibit insufficient luminescence intensity to be legible on its own. Yet, as illustrated in row515and columns513and514ofFIG.5B, color cell “A7” (“Light Blue Green”) is illustrated as inherently redundant as cell “J10” or “Rich Black” which with 100% cyan, 100% magenta, 100% yellow, and 100% black component colors is the most redundant composite process color possible for a four color (i.e., CMYK) process. The reason color cell “A7” or “Light Blue Green” is confirmed as redundant, is the exemplary illustration510ofFIG.5Bonly evaluates the resulting composite process color and not the component colors that make up cell “A7.” Therefore, to determine if a composite process color is truly suitable for printing redundant indicia, a separate analysis must be conducted in this embodiment on each of its component colors.

FIG.5Cillustrates525the same sixteen different multiple renderings of the representative color matrix500ofFIG.5Aarranged in a similar 4×4 grid as510ofFIG.5B. However, with525ofFIG.5Cthe color cyan has been removed from all of the process color cells of the matrices. Thus, for colors employing 0% cyan, no difference from510ofFIG.5Bwill be observed, but composite process colors that do employ any percentage of cyan in printing will appear different in525ofFIG.5B. Consequently, the illustration of525ofFIG.5Cisolates and highlights the composite process colors that fail indicia redundancy testing when the color cyan fails to print.

Similar to the description ofFIG.5B, in525ofFIG.5Cthe first row526renders the matrices in white light illumination, the second row527renders the matrices as perceived by human eye “red” cone photoreceptors, the third row528renders the matrices as perceived by human eye “green” cone photoreceptors, and the fourth row529renders the matrices as perceived by human eye “blue” cone photoreceptors. The four columns (530thru533) vary by how the matrices' colors are displayed, with the first column530rendering the matrices in color with the second531, third532, and fourth533columns rendering the matrices in grayscale.

In row526and columns531thru533, as before matrix color cells that are inherently non-redundant (i.e., printed with at most with one inkjet head) are highlighted with a blue cell containing the null set symbol (“Ø”). Columns532and533provide the same grayscale intensity renderings as column531, but columns532and533also apply theoretical minimum grayscale threshold tests (i.e., 15% minimum threshold test for column532and a 25% minimum threshold test for column533) to the grayscale matrices of rows:527(red intensity tests),528(green intensity tests), and529(blue intensity tests). Any matrix color cell failing the respective intensity test for rows527thru529is highlighted as a yellow cell. All matrix color cells that failed an intensity test in all three rows (527thru529) are deemed to be non-redundant and are highlighted in row526columns532and533as a red cell containing the null set symbol (“Ø”). Thus, all remaining colors not covered by a colored cell with a null set symbol (“Ø”) in row526columns532and533matrices would be considered redundant in this example525.

FIG.5Dillustrates535the same sixteen different multiple renderings of the representative color matrix500ofFIG.5Aarranged in a similar 4×4 grid; however, with535ofFIG.5Dthe color magenta has been removed from all of the process color cells of the matrices. Consequently, the illustration of535ofFIG.5Disolates and highlights the composite process colors that fail indicia redundancy testing when the color magenta fails to print.

As before, in535the first row536renders the matrices in white light illumination, the second row537renders the matrices as perceived by human eye “red” cone photoreceptors, the third row538renders the matrices as perceived by human eye “green” cone photoreceptors, and the fourth row539renders the matrices as perceived by human eye “blue” cone photoreceptors. The four columns540thru543vary by how the matrices' colors are displayed, with the first column540rendering the matrices in color with the second541, third542, and fourth543columns rendering the matrices in grayscale.

In row536and columns541thru543, matrix color cells that are inherently non-redundant (i.e., printed with at most with one inkjet head) are highlighted with a blue cell containing the null set symbol (“Ø”). Columns542and543provide the same grayscale intensity renderings as column541, but columns542and543also apply theoretical minimum grayscale threshold tests (i.e., 15% minimum threshold test for column542and a 25% minimum threshold test for column543) to the grayscale matrices of rows:537(red intensity tests),538(green intensity tests), and539(blue intensity tests). Any matrix color cell failing the respective intensity test for rows537thru539is highlighted as a yellow cell. All matrix color cells that failed an intensity test in all three rows (537thru539) are deemed to be non-redundant and are highlighted in row536columns542and543as a red cell containing the null set symbol (“Ø”). Thus, all remaining colors not covered by a colored cell with a null set symbol (“Ø”) in row536columns542and543matrices would be considered redundant in this example535.

Again,FIG.5Eillustrates545the same sixteen different multiple renderings as previously; however, with545ofFIG.5Ethe color yellow has been removed from all of the process color cells of the matrices. Consequently, the illustration of545ofFIG.5Eisolates and highlights the composite process colors that fail indicia redundancy testing when the color yellow fails to print.

As before, in545the first row546renders the matrices in white light illumination, the second row547renders the matrices as perceived by human eye “red” cone photoreceptors, the third row548renders the matrices as perceived by human eye “green” cone photoreceptors, and the fourth row549renders the matrices as perceived by human eye “blue” cone photoreceptors. The four columns (550thru553) vary by how the matrices' colors are displayed, with the first column550rendering the matrices in color with the second551, third552, and fourth553columns rendering the matrices in grayscale.

In row546and columns551thru553, matrix color cells that are inherently non-redundant (i.e., printed with only one inkjet head) are highlighted with a blue cell containing the null set symbol (“Ø”). Columns552and553provide the same grayscale intensity renderings as column551, but columns552and553also apply a theoretical minimum grayscale threshold tests (i.e., 15% minimum threshold test for column552and a 25% minimum threshold test for column553) to the grayscale matrices of rows:547(red intensity tests),548(green intensity tests), and549(blue intensity tests). Any matrix color cell failing the respective intensity test for rows547thru549is highlighted as a yellow cell. All matrix color cells that failed an intensity test in all three rows (547thru549) are deemed to be non-redundant and are highlighted in row546columns552and553as a red cell containing the null set symbol (“Ø”). Thus, all remaining colors not covered by a colored cell with a null set symbol (“Ø”) in row546columns552and553matrices would be considered redundant in this example545.

Finally,FIG.5Fillustrates555the same sixteen different multiple renderings as previously; however, with555ofFIG.5Fthe color black has been removed from all of the process color cells of the matrices. Consequently, the illustration of555ofFIG.5Fisolates and highlights the composite process colors that fail indicia redundancy testing when the color black fails to print.

As before, in555the first row556renders the matrices in white light illumination, the second row557renders the matrices as perceived by human eye “red” cone photoreceptors, the third row558renders the matrices as perceived by human eye “green” cone photoreceptors, and the fourth row559renders the matrices as perceived by human eye “blue” cone photoreceptors. The four columns (560thru563) vary by how the matrices' colors are displayed, with the first column560rendering the matrices in color with the second561, third562, and fourth563columns rendering the matrices in grayscale.

In row556and columns561thru563, matrix color cells that are inherently non-redundant (i.e., printed with at most one inkjet head) are highlighted with a blue cell containing the null set symbol (“Ø”). Columns562and563provide the same grayscale intensity renderings as column561, but columns562and563also apply i theoretical minimum grayscale threshold tests (i.e., 15% minimum threshold test for column562and a 25% minimum threshold test for column563) to the grayscale matrices of rows:557(red intensity tests),558(green intensity tests), and559(blue intensity tests). Any matrix color cell failing the respective intensity test for rows557thru559is highlighted as a yellow cell. All matrix color cells that failed an intensity test in all three rows (557thru559) are deemed to be non-redundant and are highlighted in row556columns562and563as a red cell containing the null set symbol (“Ø”). Thus, all remaining colors not covered by a colored cell with a null set symbol (“Ø”) in row556columns562and563matrices would be considered redundant in this example555.

Having previously identified the matrix color cells that are inherently non-redundant (i.e., printed with only one inkjet head—highlighted with a blue cell containing the null set symbol “Ø”) as well as the matrix color cells that are non-redundant composite process colors when either the component color cyan, magenta, yellow, or black fail to print; it remains to identify the matrix composite process color cells that are redundant for printing indicia—i.e., composite process colors where the indicia remain legible if any one component color fails to print. The most expedient method to identify the matrix composite process color cells that are redundant for printing indicia is to first identify and flag the non-redundant matrix composite process color cells from the previous examples, consequently, all remaining (i.e., non-flagged) matrix composite process color cells would then designate the colors that are redundant for printing indicia.

SinceFIG.5Cthru5F have already identified the matrix composite process color cells that fail luminescence threshold tests when either the component color cyan (FIG.5C), magenta (FIG.5D), yellow (FIG.5E), or black (FIG.5F) fail to print; logically ANDing the failed matrix color cells from all four figures with any matrix composite process color cell failing on all four figures identified as non-redundant and highlighted in row576columns582and583ofFIG.5Gwith a red cell containing the null set symbol (“Ø”).

Thus,FIG.5Gillustrates575the same sixteen different multiple renderings, highlighting the overall non-redundant colors. In575the first row576renders the matrices in white light illumination, the second row577renders the matrices as perceived by human eye “red” cone photoreceptors, the third row578renders the matrices as perceived by human eye “green” cone photoreceptors, and the fourth row579renders the matrices as perceived by human eye “blue” cone photoreceptors. The four columns (580thru583) vary by how the matrices' colors are displayed, with the first column580rendering the matrices in color with the second581, third582, and fourth583columns rendering the matrices in grayscale.

In row576and columns581thru583, matrix color cells that are inherently non-redundant (i.e., printed with at most one inkjet head) are highlighted with a blue cell containing the null set symbol (“Ø”). Columns582and583provide the same grayscale intensity renderings as column581, but columns582and583also apply i a theoretical minimum grayscale threshold tests (i.e., 15% minimum threshold test for column582and a 25% minimum threshold test for column583) to the grayscale matrices of rows:577(red intensity tests),578(green intensity tests), and579(blue intensity tests). Any matrix color cell failing the respective intensity test for rows577thru579is highlighted as a yellow cell. However, in example575ofFIG.5G, the yellow flagged failed cells of577thru579represent matrix color cells that fail luminescence threshold tests when the component color cyan (FIG.5C), magenta (FIG.5D), yellow (FIG.5E), or black (FIG.5F) fail to print logically ANDing the failed matrix color cells from all four figures resulting in any matrix composite process color cell failing on all four figures being non-redundant for indicia printing and highlighted in row576columns582and583ofFIG.5Gwith a red cell containing the null set symbol (“Ø”).

Thus, with the redundant indicia composite process colors enabled by the present disclosure with respect to human eye photoreceptor legibility, the pool of possible redundant composite process colors is modified and can be increased over known systems. For example,FIG.6depicts two representative examples of lottery-type instant ticket indicia comprised of composite process color ink applications for redundancy. Indicium600exemplifying redundant printing with a “red” composite process color (i.e., 0% cyan, 100% magenta, 100% yellow, and 0% black) as enabled by the present disclosure and indicium601′ exemplifying redundant printing with a known “rich black” composite process color (i.e., 100% cyan, 100% magenta, 100% yellow, and 100% black). Redundant indicium600(i.e., a red card symbol) was not possible under known additive model redundancy methods, since the color “red” composite process color is typically comprised of two component colors (i.e., 100% magenta and 100% yellow) and with known methods, 100% yellow was deemed to be unsuitable for indicia redundancy purposes—e.g.,FIG.1F, callouts131and132.

To better illustrate how both indicium600and known indicium600′ are both embodiments of redundantly printed indicia,FIG.6also includes three simulated color misprints—602thru604and602′ thru604′. The correctly printed portions601and601′ illustrate how the two indicia would appear with no misprints. The misprints illustrated in602and602′ are a simulation of how the two indicia would appear to a human eye if the magenta print head failed to print, the misprints illustrated in603and603′ are a simulation of how the two indicia would appear to a human eye if the yellow print head failed to print, and the misprints illustrated in604and604′ are a simulation of how the two indicia would appear to a human eye if the cyan print head failed to print. As is readily apparent in the redundant variable indicia600and600′ ofFIG.6, the absence of any these three component colors still leaves both indicia600and600′ easily legible to a human observer in its intended form. Thus, the redundant printing of the composite process colors alleviates any reasonable misinterpretation of the information conveyed by the variable indicia600and600′.

One possible press configuration700capable of producing the redundant variable indicia embodiments ofFIG.6is illustrated inFIG.7. As shown inFIG.7, press configuration700illustrates a hybrid flexographic and digital imager printing press used to produce variable indicia SOC secured documents. The industry press700unravels its paper web substrate from a roll701and flexographically prints702lower security coatings and a primer in the scratch-off area as well as optionally prints display (i.e., the region on the front of the SOC document not covered by SOC) and the back of the document's non-variable information. At this point, the press web enters a typically secured imager room where the variable indicia are applied by an imager703. However, in view of this disclosure, the imager employed would be a process color imager709(e.g., Memjet® Duralink) instead of the typical monochromatic imager. The process color imager709, having the advantage of inherent redundancy, since the imager is equipped with multiple physically discrete print heads (e.g., cyan710, magenta711, yellow712, and black713as illustrated in700) that operate independent of each other such that a failure (e.g., clogged inkjet head) in one print head will not impact the operation of the remaining print heads. Thus, with the present disclosure, the variable indicia in the SOC protected document is printed redundantly via the plurality of discrete print heads (typical of process color) so long as the composite process color(s) chosen for imaging the indicia are comprised of at least two different component colors where each component color is legible to human eye photoreceptors.

The remainder of press configuration700can remain typical of the industry standard for producing SOC protected documents with a second, typically monochromatic, imager704utilized to print the variable information presented on the back of the SOC protected document (e.g., inventory barcode). Subsequently, a series of flexographic print stations705print the upper security layers of a SOC document (e.g., a clear release coat, an upper blocking black coat, a white coating) as well as the decorative overprint (i.e., the process color or spot colors applied as an image or pattern on top of the scratch-off portion) with the web typically being rewound into a roll706for storage and ultimate processing by a separate packaging line.

It should be appreciated from the above that various embodiments of the present disclosure provide a system and method for determining and making redundantly printed process color variable indicum conveying variable information. In various embodiments, such process color variable indicum include a plurality of component colors with each component color determined with a grayscale equivalent level greater than a predetermined minimum threshold when viewed in any of red, green, or blue channels of an additive color model, such that at least two of the component colors comprising the variable indicum coveys a meaning of the variable information of the process color variable indicum when viewed in at least one channel of the additive color model. In various such embodiments, the system and method further include providing a scratch-off coating covering at least a portion of such printed variable indicia.

It should be appreciated from the above that various embodiments of the present disclosure provide a method for producing a redundantly printed security-enhanced document including a substrate with process color variable indicia representing variable information and printed on the substrate, wherein the process color variable indicia include a plurality of component colors. In various such embodiments, the method includes determining a variable indicia illuminating light color temperature. In various such embodiments, the method includes determining, utilizing an additive color model, a grayscale equivalent level of each component color of the process color variable indicia with each of Red, Green, and Blue (RGB) channels. In various such embodiments, the method includes determining each of the component colors of the process color variable indicia to ensure that the component colors exhibit a grayscale equivalent level greater than or equal to a predetermined threshold in at least one channel of an additive color model, such that a failure of the printing any one of the component colors of the process color variable indicia does not alter a meaning of the variable information represented by the other component color of the variable indicia. In various such embodiments, the method includes sending instructions intended to cause print heads to print the component colors to form the process color variable indicia on the substrate with separate print heads. In various such embodiments, the method includes applying a scratch-off coating covering at least a portion of the process color variable indicia. In various such embodiments, the predetermined threshold is 15% grayscale equivalent in at least one channel of the additive color model. In various such embodiments, the predetermined threshold is 25% grayscale equivalent in at least one channel of the additive color model. In various such embodiments, the method includes printing the process color variable indicia in four colors. In various such embodiments, the variable information relates to an intended value. In various such embodiments, the variable indicia are alphanumeric characters. In various such embodiments, the variable indicia are icons or figures. In various such embodiments, the additive color model is Adobe Photoshop (Red, Green, Blue) RGB, 8-bit. In various such embodiments, the additive color model is an Adobe Photoshop RGB, 8-bit, profile with a blue channel gamut that is attenuated 7% and a red channel gamut that is attenuated 3%. In various such embodiments, the method the illuminating light color temperature is 3,200° Kelvin (K). In various such embodiments, the method includes digitally emulating the illuminating light color temperature of 3,200° Kelvin (K) using an Adobe Photoshop RGB, 8-bit, profile.

It should be appreciated from the above that various embodiments of the present disclosure provide a redundantly printed security-enhanced document that includes a substrate, process color variable indicia representing variable information printed on the substrate, and a scratch-off coating covering at least a portion of the process color variable indicia. In various such embodiments, the process color variable indicia includes a plurality of component colors, each component color selected to manifest a grayscale equivalent level greater than a predetermined minimum threshold when viewed in any of red, green, or blue channels of an additive color model, such that at least two of the component colors of the process color variable indicia covey a meaning of the variable information of the process color variable indicia when viewed in at least one channel of the additive color model. In various such embodiments, the additive color model is Adobe Photoshop (Red, Green, Blue) RGB, 8-bit. In various such embodiments, the additive color model includes a blue channel color gamut that is attenuated 7% and a red channel color gamut that is attenuated 3%. In various such embodiments, the predetermined minimum threshold is at least a 15% grayscale equivalent in at least one channel of the additive color model. In various such embodiments, the predetermined minimum threshold is at least a 25% grayscale equivalent in at least one channel of the additive color model. In various such embodiments, the process color variable indicia is printed with four process colors. In various such embodiments, the variable information relates to an intended value. In various such embodiments, the process color variable indicia are icons or figures.

The present disclosure contemplates other variations of the disclosed embodiments (e.g., process color indicia images comprised of a balance of at least two different colors, etc.) that would be apparent to anyone skilled in the art in view of the present disclosure and would be within the parameters of the appended claims.