System and method for reading a barcode independently of image resolution or scale

The present disclosure relates to a system for reading a barcode independently of image resolution or scale of a captured barcode image. In one embodiment, the system includes an optical sensor and a processor. The optical scanner can scan a barcode, including a plurality of bars and spaces, into a scanned image. The processor can convert the scanned image into binary data. The processor can also calculate numbers of ones (1s) between zeros (0s) in the binary data and determine widths of one of i) each of the bars and ii) each of the spaces based on the calculated numbers of ones (1s). The processor can further calculate numbers of zeros (0s) between ones (1s) in the binary data and determine widths of the other one of i) each of the bars and ii) each of the spaces based on the calculated numbers of zeros (0s).

BACKGROUND

Technical Field

The described technology generally relates to image processing, and in particular to a system and method for reading a barcode independently of image resolution or scale of a captured barcode image.

Description of the Related Technology

Items, such as articles of mail (e.g., letters, flats, parcels, and the like), warehouse inventories, or packages are frequently received into a processing facility in volume, and must be sorted into particular groups to facilitate further processes such as, for example, delivery of the item to a specified destination. The particular groups can correspond to destinations or other information identified on the item. Processing items or articles can include reading and processing barcode data placed on the items or articles.

SUMMARY

The embodiments disclosed herein each have several aspects no single one of which is solely responsible for the disclosure's desirable attributes. Without limiting the scope of this disclosure, its more prominent features will now be briefly discussed. After considering this discussion, and particularly after reading the section entitled “Detailed Description,” one will understand how the features of the embodiments described herein provide advantages over existing systems, devices, and methods for image encryption through dynamic compression code words.

One aspect is a system for reading a barcode, the system comprising, a reader configured to read a barcode, positioned on a mail or parcel item, into a scanned image, the barcode including a plurality of bars and a plurality of spaces alternately disposed with respect to the plurality of bars, and a processor in data communication with the reader and configured to: convert the scanned image into binary data including a plurality of ones (1s) and a plurality of zeros (0s), wherein one (1) represents a pixel having a first characteristic and a zero (0) represents a pixel having a second characteristic; calculate numbers of ones (1s) disposed between zeros (0s) in the binary data; determine widths of one of i) each of the plurality of bars and ii) each of the plurality of spaces based on the calculated numbers of ones (1s), calculate numbers of zeros (0s) disposed between ones (1s) in the binary data; and determine widths of the other one of i) each of the plurality of bars and ii) each of the plurality of spaces basal on the calculated numbers of zeros (0s).

In the above system, the processor is further configured to compare among determined bar widths to identify a widest, bar, compare among determined space widths to identify a widest space; calculate a bar width scaling factor based on a largest width specified by a predetermined barcode standard and the identified widest bar; calculate a space width scaling factor based on the largest width specified by the predetermined barcode standard and the identified widest space; multiply the calculated scaling factors by the determined bar and space widths to obtain scaled bar and space widths; and determine adjusted width values of the bars and spaces by referencing the scaled bar and space widths against corresponding values of a predetermined barcode specification stored in a memory.

Another aspect is a system for reading a barcode independently of image resolution or scale of a captured barcode image, the system comprising: a reader configured to read a barcode, positioned on a mail or parcel item, into a scanned barcode image, the barcode including a plurality of bars and a plurality of spaces alternately disposed with respect to the plurality of bars, and a processor in data communication with the reader and configured to convert the scanned image into binary data (A) having a plurality of binary digits; subtract a lower digit binary value of the binary data (A) from an adjacent higher digit binary value of the binary data (A) throughout the plurality of binary digits so as to determine a subtracted set of the barcode data (B); select a first set of digit values (C1) having a positive digit difference from the subtracted set of the barcode data (B); select a second set of digit values (C2) having a negative digit difference from the subtracted set of the barcode data (B), and determine widths (L1) of the plurality of bars and widths (L2) of the plurality of spaces based on the first and second sets of digit values (C1, C2).

In the above system, the plurality of binary digits of the binary data (A) comprise a plurality of ones (1s) and a plurality of zeros (0s), wherein one (1) represents a pixel having a first characteristic and zero (0) represents a pixel having a second characteristic, wherein the binary data (A) is represented by a matrix of A (î, ĵ), and wherein the subtracted set of the barcode data (B) comprises 1, 0, −1 and is determined using Equation 1 below Equation 1: B=A(2≤ĵ≤nA)−A(1≤ĵ≤nA−1) where the dimension of B is 1/nBand nB=nA−1.

In the above system, the processor is further configured to select the first and second sets of digit values (C1, C2) using Equation 2 below: Equation 2: C1=ĵB(B=1) with a dimension nC1=Σ(B=1) and C2=ĵB(B=−1) with a dimension nC2=Σ(B=−1). In the above system, the processor is further configured to determine the widths (L1) of the plurality of bars using Equation 3 below: Equation 3: L1=[C2(1), C2(2≤ĵC1≤nC1)−C1(1≤ĵC2≤nC2), nA−C1(nC1)]. In the above system, the processor is further configured to determine the widths (L2) of the plurality of spaces using Equation 4 below: Equation 4: L2=C1−C2.

In the above system, the processor is further configured to: compare among determined bar widths to determine a widest bar ([L1]); compare among determined space widths to determine a widest space ([L2]); calculate a bar width scaling factor based on a largest width (Ls) specified by a predetermined barcode standard and the widest bar ([L1]) determined; calculate a space width scaling factor based on the largest width (Ls) specified by the predetermined barcode standard and the determined widest space ([L2]); multiply the calculated space width scaling factor by the determined widest bar and space widths to obtain scaled bar widths (S1) and scaled space widths (S2); and determine adjusted width values of the bars and spaces by referencing the scaled bar and space widths (S1, S2) against corresponding values of a predetermined barcode specification stored in a memory.

In the above system, the processor is further configured to determine the scaled bar widths (S1) using Equation 5 below: Equation 5: S1=(└LS┘/└L1┘)×L1or S1={(└LS┘/└L1┘)+(└LS┘/└L1┘)}/2×L1. In the above system, the processor is further configured to determine the seated space widths (S2) using Equation 6 below: Equation 6: S2=(└LS┘/└L2┘)/L2or S2={(└LS┘/└L2┘))+(└LS┘/└L2┘)}/2×L2. In the above system, the first characteristic comprises a first color and lire second characteristic comprises a second color, different from the first color.

Another aspect is a method of reading a barcode, the method comprising, reading, at a reader, a barcode, positioned on an item, into a scanned barcode image, the barcode including a plurality of bars and a plurality of spaces alternately disposed with respect to the plurality of bars; converting the read image into binary data (A) having a plurality of binary digits, subtracting, at a processor in data communication with the reader, a lower digit binary value of the binary data (A) from an adjacent higher digit binary value of the binary data (A) throughout the plurality of binary digits so as to determine a subtracted set of the barcode data (B), selecting, at the processor, a first set of digit values (C1) having a positive digit difference from the subtracted set of the barcode data (B); selecting, at the processor, a second set of digit values (C2) having a negative digit difference from the subtracted set of the barcode data (B); and determining, at the processor, widths (L1) of the plurality of bars and widths (L2) of tbc plurality of spaces based on the first and second sets of binary digit values (C1, C2).

In the above method, the plurality of binary digits of the binary data (A) comprise a plurality of ones (1s) and a plurality of zeros (0s), wherein one (1) represents a pixel having a first characteristic and zero (0) represents a pixel having a second characteristic, wherein the binary data (A) is represented by a matrix of A (î, ĵ), and wherein the subtracted set of the barcode data (B) comprises 1, 0, −1 and is determined using Equation 1 below: Equation 1: B=A(2≤ĵ≤nA)−A(1≤ĵ≤nA1) where a dimension B=1×nBand nB=nA−1.

In the above method, selecting the first and second sets of digit values (C1, C2) is performed using Equation 2 below: Equation 2: C1=ĵB(B=1) with a dimension nC1=Σ(B=1) and C2=ĵB(B=−1) with a dimension nC2=Σ(B=−1). In the above method, determining the widths (L1) of the plurality of bars is performed using Equation 3 below: Equation 3: L1=[C2(1), C2(2≤ĵC1≤nC1)−C1(1≤ĵC2≤nC2), nA−C1(nC1)]. In the above method, determining the widths (L2) of the plurality of spaces is performed using Equation 4 below: Equation 4: L2=C1−C2.

The above method, further comprises: comparing, at the processor, among determined bar widths to identify a widest bar ([L1]); comparing, at the processor, among determined space widths to identify a widest space ([L2]), calculating, at the processor, a bar width scaling factor based on a largest width (Ls) specified by a predetermined barcode standard and the determined widest bar ([L1]); calculating, at the processor, a space width scaling factor based on the largest width (Ls) specified by the predetermined barcode standard and the determined widest space ([L2]); multiplying; at the processor, the calculated width scaling factors by the determined bar and space widths to obtain scaled bar widths (S1) and scaled space widths (S2); and determining, at the processor, adjusted width values of the bars and spaces by referencing the scaled bar and space widths (S1, S2) against corresponding values of a predetermined barcode specification.

In the above method, the scaled bar widths (S1) are calculated using Equation 5 below: Equation 5: S1=(└LS┘/└L1┘)×L1or S1={(└LS┘/└L1┘)+(└LS┘/└L1┘)}/2×L1. In the above method, the scaled space widths (S2) are calculated using Equation 6 below: Equation 6: S2=(└LS┘/└L2┘)×L2or S2={(└LS┘/└L2┘))+(LS┘/└L2┘)}/2×L2.

The above method further comprises: comparing, at the processor, among calculated bar widths to determine a narrowest bar; comparing, at the processor, among calculated space widths to determine a narrowest space; calculating, at the processor, a bar width scaling factor based on a smallest width specified by a predetermined barcode standard and the narrowest bar determined; calculating, at the processor, a space width scaling factor based on the smallest width specified by the predetermined barcode standard and the narrowest space determined; multiplying, at the processor, the calculated width scaling factors by the determined bar and space widths to obtain scaled bar widths and scaled space widths; and determining, at the processor, adjusted width values of the bars and spaces by referencing the scaled bar and space widths against corresponding values of a predetermined barcode specification stored in a memory.

DETAILED DESCRIPTION

Provided herein are various embodiments of systems and methods for image processing including, for example, a system and method for reading a barcode such as an IMpb independently of image resolution or scale of a captured barcode image. Various embodiments can significantly improve measurement accuracy of dimensions of a barcode such as widths of bars (e.g., black bars) and spaces (e.g., white spaces) of the barcode regardless of image resolution or scale of a captured barcode image so that the functionality of computing devices such as an item processing system is significantly improved Such improved accuracy in reading barcode data can also enhance the encoding and decoding accuracy of barcode data.

Reference in the specification to “one embodiment,” “an embodiment,” or “in some embodiments” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Moreover, the appearance of these or similar phrases throughout the specification do not necessarily all refer to the same embodiment, nor are separate or alternative embodiments necessarily mutually exclusive. Various features are described herein which may be exhibited by some embodiments and not by others. Similarly, various requirements are described which may be requirements for some embodiments but may not be requirements for other embodiments.

As used here, the term “item” or “items” may refer to flats, letters, parcels, residual mail, and the like. Although the present disclosure describes systems and devices for image processing related to articles of mail, such as letters and flats, it will be apparent to one of skill in the art that the disclosure presented herein is not limited thereto. For example, the described technology may have application in a variety of manufacturing, assembly, distribution, or sorting applications which include processing images including personal or sensitive information at high rates of speed and volume.

Where a plurality of images are captured, large volumes of data are created. This can be the case in various applications, such as recording video, photographing items, such as archives, and other applications where multiple images are being captured. A large amount of data is generated when handling items through processing systems. Handling items can include capturing one or more images of the item as it is being processed. For example, items, such as articles of mail (e.g., letters, flats, parcels, and the like), warehouse inventories, or packages are frequently received into a processing facility in bulk, and must be sorted into particular groups to facilitate further processes such as, for example, delivery of the item to a specified destination. Sorting items or articles can be done using imaging technologies. The ability to accurately process a given item may be limited by the effectiveness of the imaging technology to extract accurate information about each item. The extracted information may include personal information about the sender or receiver of the item such as name, address, account information, or other information that is provided in trust that public disclosure will be limited if not avoided altogether. Careful handling of the personal information includes careful handling of images taken of the item during processing. Mail delivery is one example of an industrial application that relies on sorting and processing large quantities of items. Others may include, but are not limited to, retail operations with large inventories and high daily sales, high volume component manufacturers, such as consumer goods, baggage sorting, and importing operations with high volumes of imports needing sorting and receiving daily.

Mail piece or parcel items are sorted and the information (e.g., addresses, types of items, barcode, etc.) about them are scanned in an item processing facility. Thus, hereinafter, the item processing facility will be described first. A processing facility can use automated processing equipment to sort items. An item processing facility may receive a very high volume of items, such as letters, flats, parcels, or other objects which must be sorted and/or sequenced for delivery. Sorting and/or sequencing may be accomplished using item processing equipment which can scan, read, or otherwise interpret a destination end point from each item processed. The destination end point may be encoded in a computer readable code, such as a barcode printed on or affixed to the item. In some embodiments, the destination end point may be read by taking an image of the item and performing an optical character recognition (OCR) process on the image, and determining the delivery end point from the OCR'd address. In some embodiments, the item processing equipment can apply a computer readable code that encodes the delivery end point and may prim or spray the computer readable code onto the item. In some embodiments, the processing facility uses sorting/sequencing apparatuses which can process over about 30,000 items per hour.

FIG. 1illustrates an example of item processing equipment100that may be used in item processing facilities Although one type of item processing equipment is depicted inFIG. 1, the current disclosure is not limited thereto. The systems and methods described here can be applicable to the illustrated type and other types of item processing equipment without departing from the scope of the current disclosure. The item processing equipment100includes an intake system110. The intake system110may be a counter, conveyor, or other receiving structure where a stack of items115, such as letters, are brought to be fed into the item processing equipment100. The intake system110may provide a surface or surfaces on which to place the stack of items115to stage the items for processing. The item processing equipment100has a scanning portion120that includes a scanner (e.g.,820inFIG. 8) which scans or reads a computer readable code or performs OCR of an image of part or all of an item115in order to identify various characteristics of the item(s)115, such as class of service, addressee, and/or delivery end point. The item processing equipment100includes a processor (not shown) configured to control the operation of the item processing equipment100, including controlling the movement of items through the item processing equipment100via conveyor belts, pinch belts, and/or motors, controlling the scanning portion120to facilitate the intake, sorting, and sequencing the items115. The processor is in communication with a memory (not shown) where information from the scanner is stored for further use. The memory can be part of the item processing equipment100, or may be remote to the item processing equipment100. The memory may be on a network with which the processor can communicate, and the memory may be shared by different components within a processing facility. The memory is configured to store the identity of each article processed, including information scanned, read, or interpreted from the letter, such as delivery end point, sender, class of service, postage, serial number, and the like. The memory is also configured to store the sequence of items in the item stream as they are scanned.

The item processing equipment100further includes a sorting portion130. The sorting portion130may be a large storage and conveyor cabinet as shown, which has inside various components (not shown), for directing items115along particular pathways as the items115are sorted. The sorting portion130may be located adjacent to or otherwise near the intake system110. In some embodiments, the items115may be moved or transported from the intake system110to the sorting portion130by an automated system including series of pinch belts, vacuum belts, or other conveying mechanisms. As the items are moved or transported from the intake system110to the sorting portion130, the items are read or scanned, and destinations identified for each individual item115. The processor then operates a system of motors, conveyors, and pinch belts to direct the item to the output portion140.

The output portion140may be a structural system having a plurality of stackers, receptacles, pockets, output areas, or bins45arrayed, in some embodiments, in vertically disposed rows. Each bin45is configured to receive one or more items115from the soiling portion130. Each bin45can be assigned to a particular delivery route or to one or more stop groups.

Various embodiments involve reading and processing a barcode independently of image resolution or scale of a captured barcode image. Thus, hereinafter, some example barcodes will be described first. Various embodiments capture an entirety or a portion of an item containing a barcode that includes bars and spaces having different widths. Here, the bars mean lines (e.g., black lines) and the spaces mean empty spaces (e.g., white spaces) next to the bars and having a color different from that of the bars. Although various embodiments are described based on black bars and white spaces, the bars may have non-black colors and the spaces may have non-white colors, as long as the bars and spaces can be distinctively recognized by a computing device (e.g., optical scanner or controller).

A bar on a barcode has a vertically extending height and a horizontally extending width generally less than the height Barcode bars may have different or same widths. For example, the widths of at least some bars disposed between neighboring spaces may be different from those of other bars (see, for example,FIGS. 2A-4B). Similarly, barcode spaces may have different or same widths. For example, the widths of at least some spaces disposed between neighboring bars may be different from those of other spaces (see, for example,FIGS. 2A-4B). The bars and spaces may be alternately arranged in the barcode. Each barcode may have a unique arrangement of bars and spaces so as to contain a unique set of information associated with an item itself, item delivery and/or data processing, etc.

Reading a captured barcode image requires accurate sensing of dimensions (e.g., widths) of bars and spaces. However, due to different sensor resolution and/or different image scale due to different distances between sensors and barcodes being sensed, captured and sensed dimensions may not accurately reflect the accurate relative dimensions of the black bars and white spaces in the barcode. For example, based on the resolution of the camera, interpreting an image of a barcode, for example, using OCR or other techniques, the number of pixels corresponding to the width of a black or white bar, will vary from camera to camera. Thus, to property decode or read a barcode requires knowledge of the specifications and resolution of the camera. If the wrong resolution of the camera is used, the barcode reads will be errors. Thus, as described herein, it is advantageous to develop a method for reading barcodes that is agnostic about the resolution of the camera or device that captures the image of a barcode.

Various embodiments provide a system and method for accurately reading or recognizing dimensions of the bars and spaces in captured barcodes. Various embodiments further provide a system and method for compensating differences in image resolution or scale of a captured barcode image so that accurate measurement of bars and spaces can be achieved independently of image resolution or scale of a captured barcode image.

Although certain types of barcodes are described in this disclosure, various embodiments can be applied to other types of barcodes including, but not limited to, one-dimensional barcode types (e.g., UPC barcode, EAN barcode, Code39 barcode, Code 128 barcode, ITF barcode, Code 93 barcode, Codabar barcode, GS1databar barcode and MSI Plessey barcode) and two-dimensional barcodes (e.g. QR code, Datamatrix code, PDF417 code and Aztec code). Furthermore, although various embodiments are described with reference to an item barcode that is placed on a mail or an item for delivery, the present disclosure is not limited thereto and can be applied to non-mail barcodes (e.g., barcodes placed on products for sale, exhibit, or advertisement, etc.). Moreover, although various embodiments are described with reference to mail barcodes for USPS, the present disclosure is not limited thereto and can be used by other entities that ship products such as UPS, FedEx, Amazon, eBay, Uber, etc.

FIG. 2Aillustrates an example of an item barcode20according to some embodiments. The barcode20may be an Intelligent Mail® package barcode (IMpb). The IMpb is a barcode that can be read by automated parcel processing equipment and scanning devices, and includes a data string that generally follows the GS1-128 specification. The IMpb may include a variable length format that is determined by the elements selected by the sender, and supply tracking and routing data for packages and extra service applications. The IMpb may be used on commercial packages, and on other items of customers requesting extra services.

The barcode20may include an upper identification bar202, a service banner text204, an intelligent barcode200and a lower identification bar222. The intelligent barcode200may include a barcode portion212and a human-readable representation portion214. The barcode portion212may include a series of unique bars (e.g. black bars) and unique spaces (e.g., white spaces or white bars) into which data is encoded.

In some embodiments, the barcode portion212may have a GS1-128 barcode format. In other embodiments, the barcode portion212may have a format other than the GS1-128 barcode format. The GS1-128 barcode provides a global standard for exchanging data between different companies. The GS1-128 barcode not only encodes the data, but it also provides a method of defining the meaning of the data.

The elements of the IMpb may have specific dimensions. For example, as shown inFIG. 2A, each of the upper and lower identification bars202and222may have a thickness in the range of, for example, about 0.031 inches to about 0.063 inches. An upper vertical clearance208between the service banner text204and the upper identification bar202may be, for example, at least about 0.031 inches. Similarly, a lower vertical clearance218between the human-readable representation portion214and the lower identification bar222may be, for example, at least about 0.031 inches. An upper vertical clearance210between the service banner text204and the top of the barcode portion212may be in the range of, for example, about 0.125 inches to about 0.250 inches. Similarly, a lower vertical clearance216between the bottom of the barcode portion212and the human-readable representation portion214may be in the range of for example, about 0.125 inches to about 0.250 inches. A horizontal clearance206between one end of the barcode portion212and the corresponding end of each of the upper and lower identification bars202and222may be, for example, at least 10 times the X-dimension (e.g., about 0.250 inches). Each of the service banner text204and the human-readable representation number214may have a height in the range of for example, about 0.090 to about 0.125 inches. The human readable representation portion214may not extend beyond the length of the identification bars202and222. The above dimensions are merely examples and other dimensions are also possible. Some embodiments consider at least one of the above-described dimensions in reading and/or scaling the widths of the bars and spaces. Other embodiments may not consider the above-described dimensions in leading and/or scaling the widths of the bars and spaces. These embodiments may consider other factors such as relative dimensions of the bars and spaces and/or standardized barcode dimensions.

The barcode20shown inFIG. 2Ais merely an example and may include other information and/or may have different configurations, formats, barcode types, encoding schemes, or dimensions. Furthermore some information or elements can be removed from the barcode20. This applies to barcodes shown inFIGS. 3A-4B.

FIG. 2Billustrates an example of an intelligent barcode200that can be used for an item according to some embodiments. The intelligent barcode200may have a GS1-128 format, but could have another format without departing from the scope of this application. The barcode200includes black bars222and white spaces224, and a human-readable representation portion214. Each of the black bars222and the white spaces224may have a certain dimension including a width (hereinafter to be interchangeably used with “X-dimension”) and a height (hereinafter to be interchangeably used with “barcode height”). For example, the width may be in the range of about 0.013 inches to about 0.021 inches. The height may be at least about 0.75 inches. The barcode200may have a certain length230. The entire barcode length230may be a function of the number of characters encoded and the X-dimension used. Some embodiments may or may not consider the dimensions of the bars and spaces in reading and/or scaling the widths of the bars and spaces. These embodiments may consider other factors such as dimensions of at least one of the non-bar and non-space items, e.g.,202-210and/or214-218shown inFIG. 2A. Other embodiments may consider the entire barcode length230in reading, and/or scaling the widths of the bars and spaces. Still other embodiments may consider predetermined standardized dimensions in reading and/or scaling the widths of the bars and spaces.

FIG. 3Aillustrates another example of an item barcode32according to some embodiments. The barcode32may include a barcode portion322. The barcode portion322can be defined according to a barcode data format portion324. The barcode data format portion324can define portions of the barcode portion322as encoding, for example, a start code, a routing application identifier, a zip code, a check digit, a stop code, etc. In some embodiments, the barcode portion322may be separately provided on distribution items (e.g., mailpieces, parcels, etc.). The barcode portion322may have a postal routing GS1-128 barcode format that has been adopted by USPS, but may have another format as well. In some embodiments, the barcode portion322may have a fixed length326. These embodiments may consider the entire barcode length326of the barcode portion322in reading and/or scaling the widths of the bars and spaces of the barcode portion322. Other embodiments may consider predetermined standardized dimensions in reading and/or scaling the widths of the bars and spaces of the barcode portion322.

FIG. 3Billustrates another example of an item barcode34according to some embodiments. The barcode34has a barcode portion342which encodes data according to a barcode data format portion344. The barcode data format portion344can define segments of the barcode portion342as corresponding to a start code, a routing identifier, a zip code, a channel application identifier, a service type code, a mailer ID (MID), a serial number, one or more check digits, a stop code, etc. The barcode portion342may have a confirmation services concatenated GS1-128 barcode formal that has been adopted by USPS. In some embodiments, the barcode portion342may have a certain length346. Some embodiments may consider the entire barcode length346of the barcode portion342in reading and/or scaling the widths of the bars and spaces of the barcode portion342. Other embodiments may consider predetermined standardized dimensions in reading and/or scaling the widths of the bars and spaces of the barcode portion342.

FIG. 3Cillustrates another example of an item barcode36according to some embodiments. The barcode36may include a barcode portion362which is encoded according to a barcode data format portion382having fields as shown inFIG. 3C. The barcode portion362may be used to place both a postal routing barcode and a USPS Tracking barcode or signature confirmation barcode described above. The barcode portion362may have a confirmation services GS1-128 barcode format using a separate postal routing that has been adopted by USPS.

In some embodiments, the barcode portion362may have a certain length368. These embodiments may consider the entire barcode length368of the barcode portion362in reading and/or scaling the widths of the bars and spaces of the barcode portion362.

In some embodiments, the barcode portion362may include a first barcode portion364and a second barcode portion366that respectively have lengths370and372. The first and second barcode portions364and366may be spaced apart by a middle space length374. These embodiments may consider one or more of the lengths370-374in reading and/or scaling the widths of the bars and spaces of the barcode portion362. Other embodiments may consider predetermined standardized dimensions in reading and/or scaling the widths of the bars and spaces of the barcode portion362.

FIG. 4Aillustrates another example of an item barcode40according to some embodiments. The barcode40may include a barcode portion410, e.g., printed in the 24-digit format. The barcode portion410can be used on containers, items, and the like in the distribution network. For example, the barcode portion410can be used on trays, sacks, bins, pallets, and the like to uniquely identify each item and to identify a mailer or mail preparer for the item. The barcode40may be implemented with an Intelligent Mail® tray label available from USPS.

In some embodiments, the barcode portion410may have a certain length412. These embodiments may consider the entire barcode length412of the barcode portion410in reading and/or scaling the widths of the bars and spaces of the barcode portion410.

In other embodiments, the barcode40may include mailer sections414and416, for example, on the upper and lower portions thereof. These embodiments may consider one or more of the lengths of the mailer sections414and416in reading and/or scaling the widths of the bars and spaces of the barcode portion410. Other embodiments may consider predetermined standardized dimensions in reading and/or scaling the widths of the bars and spaces of the barcode portion410.

FIG. 4Billustrates another example of an item barcode42according to some embodiments. The barcode42may include a barcode portion420that can be used to identify items in the distribution network such as pallets, rolling stock, containers, such as all-purpose containers, and the like. For example, the mail barcode42may be used to uniquely identify each container and may be scanned at induction points. The mail barcode42may be implemented with, for example. Intelligent Mail container label available from USPS.

In some embodiments, the barcode42may also include upper and lower identification bars422and424, and the mailer section426. These embodiments may consider one or more of the lengths of the identification bars422and424and the mailer section426in reading and/or scaling the widths of the bars and spaces of the barcode portion420. Other embodiments may consider predetermined standardized dimensions in reading and/or scaling the widths of the bars and spaces of the barcode portion420.

FIG. 5illustrates an intelligent barcode50according to some embodiments. The barcode50may be a four-state barcode, in which data is encoded using four types of bars. For example, the barcode50includes descender bars510, tracker bars520, full bars530, and ascender bars540. The barcode50may be designed for use in high-speed, automated mail sortation machines. The barcode50may be implemented with, for example, an intelligent barcode available from USPS.

In some embodiments, all of the descender bars510, tracker bars520, full bars530, and ascender bars540may have the same width. The spaces between the bars510-540may have different widths. Some embodiments may measure or sense the heights of the bars510-540and/or the widths of the spaces between the bars510-540. The barcode50can be an Intelligent Mail® barcode (IMb) and can have segments encoding various pieces of information, as desired.

FIG. 6illustrates an example image showing an item60that contains a barcode610according to some embodiments. The item60may be processed by the system shown inFIG. 1, 8 or 9. The barcode610may be one of the barcodes described with respect toFIGS. 2A-5.

The barcode610may have a certain length612. Some embodiments may consider the entire barcode length612of the barcode610in reading and/or scaling the widths of the bars and spaces of the barcode610. Other embodiments may capture mailer sections620and630, and postage section640separately from or together with the barcode610, and consider the dimensions of one or more of the mailer sections620and630and the postage section640in reading and/or scaling the widths of the bars and spaces of the barcode610.

FIG. 7illustrates another example image showing another item70that contains barcodes710and720according to some embodiments. The item70may be processed by the system shown inFIG. 1, 8 or 9. Each of the barcodes710and720can be implemented with one or more of the barcodes described with respect toFIGS. 2A-5. Similarly to the above embodiments, parameters of one of more of several items such as the entire barcode length and dimension of mailer/postage section and other non-barcode sections, or dimensions of standardized parameters may be used in reading and/or scaling the widths of the bars and spaces of each of the barcodes710and720.

Some embodiments provide systems and methods for reading a barcode independently of image resolution or scale of a captured barcode image to significantly improve measurement accuracy of widths of black bars and white spaces of an item barcode regardless of image resolution or scale of a captured barcode image.

FIG. 8illustrates an item processing system80for processing items such as flat items containing one or more barcodes according to some embodiments. The item processing system80may be pan of the item processing equipment100ofFIG. 1or can be separately provided, for example, to be disposed adjacent thereto. The item processing system80may include processing equipment810, an optical scanner (an imaging device, an image capturing device or a reader)820, a controller850and a memory860. The item processing system80shown inFIG. 8is merely an example processing system, and certain elements may be modified or removed, and/or other elements or equipment may be added. Although only one optical scanner is shown inFIG. 8, two or more optical scanners can be provided depending on the embodiment.

The processing equipment810may be an automated letter sorting machine used for letter-size mails, sorting parcels, etc. that have computer readable codes thereon. The processing equipment810may include a conveyor belt (not shown) that moves items from one location to another. AlthoughFIG. 8shows that the optical scanner820scans letters or flat items being conveyed by the processing equipment810, the optical scanner820can also scan items such as parcels, residual mail, and the like.

The processing equipment810may process items840by conveying each proximate to or past an optical scanner820captures an image of an item830that is being conveyed. The optical scanner820may capture an entirety or a portion of one side of the item830facing the scanner820. The optical scanner820may capture information relevant to processing and/or delivery including, but not limited to, names and addresses of senders and recipients, postage and barcodes, etc. The barcodes may include an IMpb or other barcodes described above.

In some embodiments, the captured image may include one or more of the images20,200,32,34,36,40,42,50,60, and70shown inFIGS. 2A-7. In other embodiments, the captured image may include only barcode portions212,322,342,362,410,420,610,710or720shown inFIGS. 2A-7.

The optical scanner820may continuously and separately capture images of items being transported in front of the scanner820. In some embodiments, the captured images or digital data thereof may be stored in the memory860being in data communication with the controller850. In other embodiments, the captured images or digital data thereof may be stored in a memory of the scanner820or a memory of the controller850. The optical scanner820may be connected to the controller850either by wire or wirelessly. In other embodiments, the captured images or digital data thereof may be stored in a network memory such as a cloud or other device separately located from the elements820,850and860. The captured images or digital data thereof may also be transmitted to a receiving device via a communication network (wired or wireless). The digital data may include binary data. For example, “0” represents a white pixel and “1” represents a black pixel, or vice versa. Hereinafter, for the purpose of convenience, binary data will be described as an example of digital data.

In some embodiments, at least one of the scanner820or the controller850may read and process the dimensions of a barcode placed on an item. In other embodiments, at least one of the scanner820or the controller850may read and process the dimensions of a barcode independently of image resolution or scale of a captured barcode image to significantly improve measurement accuracy of dimensions of bars and spaces of the barcode.

FIG. 9illustrates a simplified depiction of an item processing system90for processing items such as parcel items containing one or more barcodes according to some embodiments. The item processing system90may include a conveyor915, a front scanner925and an upper scanner935. In some embodiments, the item processing system90may have only a front scanner925or an upper scanner935. The conveyor915conveys parcels including a parcel940and a parcel960. The front scanner925may scan a label950containing a barcode and disposed on the front side of the parcel940. The upper scanner935may scan a label (not shown) containing a barcode and disposed on the top surface of the parcel940. For the purpose of convenience, a controller and a memory are omitted inFIG. 9.

FIG. 10is a conceptual diagram showing a barcode reading procedure according to some embodiments. In some embodiments, the procedure may be performed by at least one of the optical scanner (820/925/935) or the controller850. In other embodiments, the procedure may be performed by another computing device separate from and/or in data communication with at least one of the optical scanner (820/925/935) or the controller850.

Referring toFIG. 10, a barcode1010is scanned and binarized (1020). In some embodiments, the scanner820may scan the barcode1010and binarize the scanned barcode image. In other embodiments, the scanner820may scan the barcode1010and the controller850may binarize the scanned barcode image.

In some embodiments, leading and trailing zeros have been removed in the extracted barcode. In some embodiments, black pixels may be represented as ones and white pixels may be represented as zeros. In these embodiments, black bars can be represented as a series of ones. The numbers of ones in the series may be associated with the dimensions of the bars such as widths. For example, the more consecutive ones there are, the wider the black bars are, whereas the less consecutive ones there are, the narrower the black bars. Furthermore, in these embodiments, white spaces can be represented as a series of zeros. The numbers of zeros in the series may be associated with the dimensions of the spaces such as widths. For example, the more consecutive zeros there are, the wider the white spaces are, whereas the less consecutive zeros there are, the narrower the white spaces are.

In some embodiments, black pixels may be represented as zeros and white pixels may be represented as ones. In these embodiments, black bars can be represented as a series of zeros. The numbers of zeros in the series may be associated with the dimensions of the bars such as widths. For example, the more consecutive zeros there are, the wider the black bars are, whereas the less consecutive zeros there are, the narrower the black bars. In these embodiments, white spaces can be represented as a series of ones. Again, the quantity of ones in the series may be associated with the dimensions of the spaces such as widths. For example, the more consecutive ones there are, the wider the white spaces are, whereas the less consecutive ones there are, the narrower the white spaces.

The binarized barcode data may be represented as, for example, 1,1,1,0,0,1,0,0,0,1,1,0,0,1,1. For the purpose of convenience, it is assumed that white pixels are represented as zeros and black pixels are represented as ones inFIG. 10. Furthermore, all leading and trailing zeros are removed from the binarized barcode data (A). Referring toFIG. 10, the binarized barcode data (A) includes three consecutive ones, two consecutive zeros, a single one, three consecutive zeros, two consecutive ones, two consecutive zeros and two consecutive ones in this order. For convenience, the binarized barcode data (A) is shown up to the 15thdigit. In some embodiments, the binarized barcode data can include more than 15 digits. In this example, the barcode data (A) has a format in which the widest black bar (111), the second widest white space (00), the narrowest black bar (1), the widest white space (000), the second widest black bar (11), the second widest white space (00) and the second widest black bar (11) are arranged in this order. Again, these binary values are merely an example and other combination of binary values are also possible.

Adjacent binary values of the binarized barcode data (A) may be subtracted from each other (1030). For example, since the first and second binary values are respectively 1 and 1 in the binary data (A), the first difference (or first subtracted value) would be 0 (1−1=0). Furthermore, since the second and third binary values are respectively 1 and 1 in the binary data (A), the second difference (or second subtracted value) would be also 0 (1−1=0). Moreover, since the third and fourth binary values are respectively 1 and 0 in the binary data (A), the third difference (or third subtracted value) would be −1 (0−1=−1). Repeating this for the remaining binary values in the binary data (A) would give a set of subtracted binary values (B), where B=0 0 −1 0 1 −1 0 0 1 0 −1 0 1 0. Note that since A has a 15thdigit binary value, B has a 14thdigit value.

In the subtracted data set or barcode data (B), 0 may mean that there is no change in pixel values or no changes in bar or space arrangement (same black bar or same white space arranged consecutively). Alternatively, 0 in the subtracted data set (B) may mean that the same color of pixels are consecutively arranged (e.g., two consecutive black pixels (1 1) or two consecutive white pixels (0,0)). 1 in the subtracted data set (B) may mean that there is a change in pixel values from zero to one or a change in bar or space arrangement from the white space to the black bar. Alternatively, 1 in the subtracted data set (B) may mean that a white pixel (0) and a black pixel (1) are arranged in this order (e.g., 1−0=1). −1 in the subtracted data set (B) may mean that there is a change in pixel values from one to zero or a change in bar or space arrangement from the black bar to the white space. Alternatively, −1 in the subtracted data set (B) may mean that a black pixel (1) and a white pixel (0) are arranged in this order (e.g., 0−1=−1).

In some embodiments, C may be defined as an order number set indicating the order of the subtracted barcode data (B). For example, C can be 1 2 3 4 5 6 7 8 9 10 11 12 13 14 that respectively correspond to numbers of the subtracted data set (B)=0 0 −1 0 1 −1 0 0 1 0 −1 0 1 0. For example, the first two zeros (0 0) in the subtracted barcode data (B) correspond to the first and second in order front the beginning of the order number set1032(C). The first negative one (−1) in the subtracted barcode data (B) corresponds to the third in the order number set (C). Similarly, the first positive one (1) in the subtracted barcode data (B) corresponds to the fifth in the order number set (C). In these embodiments, a leading edge1034may be represented as C1=5 9 13, and a trailing edge may be represented as C2=3 6 11, where the numbers 5, 9, 13, represent the position in the sequence of binarized data of the pixel corresponding to the leading edge of a black or white bar. Here, the leading edge (C1) means a list of binary values having B being 1 (i.e., fifth (5), ninth (9) and thirteenth (13) digit values in the subtracted barcode data (B)). Furthermore, the trailing edge1036(C2) means a list of binary values having B being −1 (i.e. third (3), sixth (6) and eleventh (11) digit values in the difference data (B)).

In some embodiments, the widths of the bars may be determined by calculating the numbers of 1s disposed between 0s in the barcode data (A). For example, as shown inFIG. 10, since there are three 1s, one 1, two 1s and two 1s disposed between 0s in this order in the barcode data (A), the widths of the bars1038(L1) may be represented as 3 1 2 2 (it is assumed that there are zeros before 111 for the purpose of convenience). These numbers (3 1 2 2) can be processed by a computing device such as the controller850to show the relative widths of the bars, for example, 3 being widest, 2 being second widest and 1 being narrowest.

In some embodiments, the widths of the spaces may be determined by calculating the numbers of 0s between 1s in the barcode data (A). For example, as shown inFIG. 10, since there are two 0s, three 0s and two 0s between 1s in this order in the barcode data (A), the widths of the spaces1040(L2) can be represented as 2 3 2. These numbers (2 3 2) can be processed by a computing device such as the controller850to show the relative widths of the spaces, for example, 3 being wider titan 2.

In another embodiment, the widths (L1, L2) of the bars and spaces may be obtained using a vector matrix and associated equations. A single row vector of an extracted barcode may be referred to as a matrix A with dimensions of using the traditional matrix indexing of A (î, ĵ). In some embodiments, the binarized barcode data (A) can have a format of a 1×15 matrix where A=[1,1,1,0,0,1,0,0,0,1,1,0,0,1,1]. Again, for the purpose of convenience, it is assumed that white pixels are represented as zeros and black pixels are represented as ones. Furthermore, all leading and trailing zeros are removed from the barcode data (A), and the barcode data (A) is shortened to a 15thdigit value.

The difference in values (or subtracted values) across the vector index can be obtained from the barcode data (A). Some embodiments use matrix arithmetic over the traditionally nested loop that can be highly optimized for some programming languages and even offer hardware acceleration.

In some embodiments, the difference vector or subtracted set of binary data (B) between adjacent binary values may be expressed in a vector form, for example, using Equation 1 below:
B=A(2≤ĵ≤nA)−A(1≤ĵ≤nA−1) where the dimension ofBis 1×nBandnB=nA−1  Equation 1
Again, since matrix A has a 1×15 matrix format, B has a 1×14 matrix format. Using Equation 1, the difference vector (B) can be calculated by using the relationship of B=A(2:end)−A(1:end−1) to obtain B(1×14)=0 0 −1 0 1 −1 0 0 1 0 −1 0 1 0. Here, A(2:end)−A(1:end−1) means that a lower digit binary value of the barcode data (A) is subtracted from an adjacent higher digit binary value of the barcode data (A) throughout all digits, for example, A2−A1 (1−1=0), A3−A2 (1−=0), A4−A3 (0−1=1), . . . , A14−A13 (1−0=1) and A15−A14 (1−1=0) to obtain the difference vector B (1×14)=0 0 −1 0 1 −1 0 0 1 0 −1 0 1 0. As the input vector (A) is binary, the resulting calculation vector of H will be a set of values selected from elements {−1,0,1}. The subtracted vector (B) can provide a method of edge type detection to determine the index locations of positive or negative change as discussed above.

A leading edge data vector (C1) and a trailing edge data vector (C2), can be calculated using Equation 2 below.
C1=ĵB(B=1) with the dimension ofnC1=Σ(B=1) andC2ĵB(B=−1) with the dimension ofnC2=Σ(B=−1)  Equation 2

With nC1=nC2provided that A (ĵ=[1, nA])=1 and the order vector of the subtracted vector (B) defined as C (1×14)=1 2 3 4 5 6 7 8 9 10 11 12 13 14, the leading edge vector can be obtained as C1(1×3)=5 9 13, and the trailing edge vector can be obtained as C2(1×3)=3 6 11.

Assuming again that the input vector (A) begins and ends with bars (i.e. all white spaces have been removed), the bar widths (L1) may be calculated using Equation 3 below.
L1=[C2(1),C2(2≤ĵC1≤nC1)−C1(1≤ĵC2≤nC2),nA−C1(nC1)]  Equation 3:

L1can be simplified as [C2(1), C2(2)−C1(1), numel(A)−C1(end)]. C2(1) means the first digit value (3) in the trailing edge matrix vector (C2) (3 6 11). C2(2)−C1(1) can be calculated by subtracting the first digit value (5) of the leading edge matrix vector (C1=5 9 13) from the second digit value (6) in the trailing edge matrix vector (C2=3 6 11) (6−5=1) and by subtracting the second digit value (9) in the leading edge matrix vector (C1=5 9 13) from the third digit value (11) of the trailing edge matrix vector (C2=3 6 11)(1−9=2). Since the first subtraction value is 1 and the second subtraction value is 2. C2(2)−C1(1) is 1 2. numel(A)−C1(end) can be calculated by subtracting the last digit value (13) of the leading edge matrix vector (C1=5 9 13) from the total digits of the barcode data (A) (15) which is 2 (15−13=2). Combining the values calculated above gives the widths of the bars (L1) as 3 1 2 2.

The space widths (L2) may be calculated using Equation 4 below.
L2=C1−C2Equation 4
Since the leading edge matrix vector can be represented as C1=(5, 9, 13) and the trailing edge matrix vector can be represented as C2=(3, 6, 11), the widths of the spaces (L2) can be obtained as the subtraction (C1−C2) which is 2 3 2 (5−3=2, 9−6=3, 13−11=2).

The system can then determine the length and position of bars and spaces of the read barcode which resulted in matrix A, by using L1and L2. The system can then use the constructed barcode to determine the value encoded by the read barcode.

Depending on the embodiments, various barcode binarization methods can lead to black bars and/or white spaces being eroded (e.g., smaller) or dilated (e.g., bigger). For a given image, the dilation may appear to be consistent resulting in all bars or white spaces being dilated or eroded in a similar ratio. Some embodiments may take the resulting width calculations for both bars and spaces and comparing the widest bar and space widths └L1┘ and └L2┘ of the vector to the largest width └LS┘ specified by the barcode standard being decoded and using that scaling factor and multiplying it by the remaining width measurements. This can be done independently tor both bar and space calculations. Additionally, a scaling factor may also be calculated using the minimum width specified for additional robustness.

In some embodiments, a bar width scaling factor can be expressed, for example, as a ratio of a largest width (└LS┘) specified by a predetermined barcode standard to the widest bar (└L1┘) measured or as a ratio of a smallest width (└LS┘) specified by a predetermined barcode standard to the narrowest bar (└L1┘) measured. Scaled bar widths (S1) can be calculated using Equation 5 below.
S1=(└LS┘/└L1┘)×L1orS1={(└LS┘/└L1┘)}/2×L1(hereinafter, └LS┘/└L1┘ or {(└LS┘/└L1┘)+(└LS┘/└L1┘)}/2 will be interchangeably used with “bar width scaling factor”).  Equation 5

In some embodiments, a space width scaling factor can be expressed, for example, as a ratio of the largest standard width (└LS┘) to the widest space (└L2┘) measured or as a ratio of a smallest width (└LS┘) specified by a predetermined barcode standard to the narrowest space (└L2┘) measured. In some embodiments, scaled space widths (S2) can be calculated using Equation 6 below.
S2=(└LS┘/└L2┘)×L2orS2{(└LS┘/└L2┘)+(└LS┘/└L2┘)}/2×L2(hereinafter, └LS┘/└L2┘ or {(└LS┘/└L2┘)+(└LS┘/└L2┘)}/2 will be interchangeably used with “space width scaling factor”).  Equation 6

In some embodiments, the scaled bar widths (S1) and the scaled space widths (S2) may be referenced against the desired barcode specification's lookup table to calculate corresponding alpha-numeric values (e.g., adjusted or compensated values of the measured bars and spaces).

Although various embodiments use a ratio of a largest standard width to a widest bar/space measured as bar/space scaling factors (└LS┘/└L1┘, └LS┘/└L2┘, {(└LS┘/└L1┘)+(└LS┘/└L1┘)}/2, {(└LS┘/└L2┘))+(└LS┘/└L2┘)}/2), many other scaling factors can also be used.

In other embodiments, various dimensions of barcode elements discussed above with respect toFIGS. 2A-7can also be used to calculate bar/space scaling factors. In some embodiments, for example when analyzing a 4-state barcode, the processes above can be performed on a plurality of pixels or binary data in rows of an image of the barcode to identify where the rising, falling, short, and tall bars are located. In some embodiments, a process similar to that described above can be performed using columns of pixel data to identify the length of bars in a 4-state barcode. To identify the length of the barcode, the above algorithms can be adapted to identify the leading edge by determining where a long suing of pixels of one color, for example, 0s in the binary data, transition to a shorter string of pixels of another color, for example, 0s in the binary data. The trailing edge can be determined by identifying where a string of pixels of one color, for example 1s in the binary data, transition to a longer string of pixels of another color, for example, 0s in the binary data. The length of the shorter string of pixels, or 1s in the binary data, can be the length of the bar in a 4-state bar code. In this embodiment the process or algorithm may not identify multiple bars in line of binary data, but will identify only the length of a single bar in a column of pixels. The algorithm can then use data from other adjacent or nearby columns of pixel data to interpret the barcode in the order of the bars.

In some embodiments, the processes ofFIG. 10can be performed to identify the number of bars in a 4-state barcode, and then the columns of pixel data can be evaluated using similar processes to identify the height of the bars in a 4-state barcode.

FIG. 11is a process flow diagram1000of a method for reading a barcode according to some embodiments. In some embodiments, the process flow diagram1000may be performed by at least one of the optical scanner (820/925/935) or the controller850. In other embodiments, the process flow diagram1000may be performed by a computing device separate from and/or in data communication with at least one of the optical scanner (820/925/935) and the controller850. Although the process flow diagram1000is described herein with reference to a particular order, in various embodiments, states herein may be performed in a different order, or omitted, and additional states may be added. This may apply to the process flow diagrams1100,1200and1300shown inFIGS. 12-14.

In state1050, the controller850may receive or retrieve binary data of the barcode data such as scanned and binarized barcode data in matrix A=(1,1,1,0,0,1,0,0,0,1,1,0,0,1,1) as shown inFIG. 10. In state1060, the controller850may calculate the numbers of 1s disposed between 0s in the barcode data (A), for example, using one or more of the processes described with respect toFIG. 10. In state1070, the controller850may determine widths of one of 1) each of the plurality of bars and 2) each of the plurality of spaces based on the calculated numbers of 1s in the barcode data (A). In some embodiments, the widths of the bars may be determined, by calculating the numbers of 1s disposed between 0s in the barcode data (A), when 1 represents a black pixel (bar) and 0 represents a white pixel (space) as described above with respect toFIG. 10. In other embodiments, the widths of the spaces may be determined by calculating the numbers of 1s between 0s in the barcode data (A), when 1 represents a white pixel (space) and 0 represents a black pixel (bar) as described above with respect toFIG. 10.

In state1080, the controller850may calculate the numbers of 0s disposed between 1s in the barcode data (A). In state1090the controller850may determine widths of the other one of 1) each of the plurality of bars and 2) each of the plurality of spaces based on the calculated numbers of 1s in the barcode data (A). In some embodiments, the widths of the spaces may be determined by calculating the numbers of 0s disposed between 1s in the barcode data (A), when 1 represents a black pixel (bar) and 0 represents a white pixel (space). In other embodiments, the widths of the bars may be determined by calculating the numbers of 0s disposed between 1s in the barcode data (A), when 1 represents a white pixel (space) and 0 represents a black pixel (bar).

FIG. 12is another process flow diagram1100of a method for reading a barcode according to some embodiments. For the purpose of the convenience, the description will be made based on the controller850performing the process flow diagram1100.

In state1110, the controller850may receive or retrieve binary data of the barcode data such as scanned and binarized barcode data (A) (1,1,1,0,0,1,0,0,0,1,1,0,0,1,1) as shown inFIG. 10. In state1120, the controller850may calculate subtracted barcode data such as the subtracted set of barcode data (B) (0 0 −1 0 1 −1 0 0 1 0 −1 0 1 0), for example, using at least one of the processes described with respect toFIG. 10. In state1130, the controller850may determine the leading edge of the subtracted set of barcode data (B) such as C1(5 9 13) as shown inFIG. 10, for example, using Equation 2 described above with respect toFIG. 10. In state1140, the controller850may determine the trailing edge of the subtracted set of barcode data (B) such as C2(3 6 11) as shown inFIG. 10, for example, using Equation 2 described above with respect toFIG. 10. In state1150, the controller850may determine the widths (L1) of the bars using, for example. Equation 3 described above with respect toFIG. 10. In state1160, the controller850may determine the widths (L2) of the spaces, for example, using Equation 4 described above with respect toFIG. 10.

FIG. 13is a process flow diagram1200of a method for scaling a barcode that has been read according to some embodiments. As discussed above, on certain embodiments, imaged black bars and white spaces can be eroded or dilated compared to their actual dimensions in the barcode. Some embodiments, as shown inFIG. 13andFIG. 14, may calculate scaled bar and space widths and determine adjusted or compensated width values of the bars and spaces by referencing the scaled bar and space widths against predetermined values.

For the purpose of the convenience, the description will be made based on the controller850performing the process flow diagram1200. In state1210, the controller850may compare among calculated bar widths to determine the bar having the largest width (or widest bar). In state1220, the controller850may compare among calculated space widths to determine the space having the largest width (or widest space).

In state1230, the controller850may calculate bar and space width scaling factors based on, for example, a largest width specified by a predetermined barcode standard and the widest bar/space determined. For example, the controller850may use, as the bar width scaling factor, a ratio of a largest width specified by a predetermined barcode standard to the widest bar determined. Furthermore, the controller850may use, as the space width scaling factor, a ratio of the largest width specified by the predetermined barcode standard to the widest space determined. Scaled bar and space widths (S1, S2) can be calculated using Equations 5 and 6 described above with respect toFIG. 10. In state1240, the controller850may multiply the scaling factors by the measured bar and space widths to obtain scaled bar and space widths (S1, S2). In state1250, the controller850may determine adjusted or compensated width values of the bars and spaces, for example, by referencing the scaled bar and space widths (S1, S2) against corresponding values in a barcode specification's lookup table.

FIG. 14is another process flow diagram1300of a method for scaling a barcode data that has been read according to some embodiments. For the purpose of the convenience, the description will be made based on the controller850performing the process flow diagram1300. In state1310, the controller850may compare among calculated bar widths to determine the bar having the smallest width (or narrowest bar). In state1320, the controller850may compare among calculated space widths to determine the space having the smallest width (or narrowest space).

In state1330, the controller850may calculate scaling factors, for example, represented as ratios of a smallest width specified by a predetermined barcode standard to the smallest bar/space determined, for example, using a method similar to that described with respect toFIG. 13. Instate1340, the controller850may multiply the calculated scaling factors by the determined bar and space widths to obtain the scaled bar and space widths. In state1350, the controller850may determine adjusted or compensated width values by referencing the scaled bar and space widths against corresponding values in a barcode specification's lookup table as described above with respect toFIG. 13.

FIG. 15is a block diagram of an embodiment of a computing device900for implementing the barcode reading methods described above.FIG. 15is merely an example block diagram of the computing device900, and certain elements may be removed, other elements added, two or more elements combined or one element can be separated into multiple elements depending on the specification and requirements.

The computing device900can be a server or other computing device, and can include a processing unit or processor902, an image feature processor930, a network interface904, a computer readable medium drive906, an input/output device interface908, and a memory910. In some embodiments, the computing device900may implement the features of one or more of the optical scanners820/925/935and the controller850. In other embodiments, at least some elements of the computing device900may be included in one or more of the optical scanners820/925/935and the controller850to perform an entirety or part of processes described herein. In still other embodiments, the computing device900may be in data communication with one or more of the optical scanners820/925/935and the controller850to perform an entirety or part of the procedures described herein.

The network interface904can provide connectivity to one or more networks or computing systems. The network interface904can receive information and instructions from other computing systems or services via the network interface904. The network interface904can also store data directly to the memory910. The processing unit902can communicate to and from the memory910and output information to an optional display918via the input/output device interface908. The input/output device interface908can also accept input from the optional input device920, such as a keyboard, mouse, digital pen, microphone, mass storage device, etc.

The memory910may contain computer program instructions that the processing unit902executes in order to implement one or more of the embodiments described above. The memory910generally includes RAM, ROM, and/or other persistent, non-transitory computer readable media. The memory910can store an operating system912that provides computer program instructions for use by the processing unit902or other elements included in the computing device in the general administration and operation of the computing device900. The memory910can further include computer program instructions and other information for implementing aspects of the present disclosure.

For example, in one embodiment, the memory910includes an image feature configuration914. The image feature configuration914may include one or more desired orientations for displaying different types of items, regular expressions for sets of characters including the routing information (e.g., ZIP code), area(s) of pre-printed packaging material that may include address information or other routing information, or other information supporting the image based routing of items described herein. The image feature configuration914may store specific values for a given configuration. The image feature configuration914may, in some embodiments, store information for obtaining values for a given configuration. For example, an address information extraction service implementing the regular expressions for identifying the address information or identify destination location information extracted from an image may be specified as a network location (e.g., URL) in conjunction with username and password information to access the service. In such embodiments, a message including the extracted text (or portion thereof) may be provided to the service. A response message may include the extracted address or destination location information, if available.

The memory910may also include or communicate with one or more auxiliary data stores, such as data store922. The data store922may electronically store data regarding mail pieces image files, or finalization results therefore.

The elements included in the computing device900may be coupled by a bus990. The bus990may be a data bus, communication bus, or other bus mechanism to enable the various components of the computing device900to exchange information.

In some embodiments, the computing device900may include additional or fewer components than are shown inFIG. 15. For example, a computing device900may include more than one processing unit902and computer readable medium drive906. In another example, the computing device900may not be coupled to a display918or an input device920. In some embodiments, two or more computing devices900may together form a computer system for executing features of the present disclosure.

In some embodiments, a non-transitory computer readable medium having stored thereon instructions which when executed by at least one computing device performs all or a portion of the methods described.

The various illustrative logical blocks, modules, routines, and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or as a combination of electronic hardware and executable software. To clearly illustrate this interchangeability, various illustrative components, blocks, modules, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as specialized hardware, or as specific software instructions executable by one or more hardware devices, depends upon the particular application and design constraints imposed on the overall system. The described functionality can be implemented in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosure.

Moreover, the various illustrative logical blocks and modules described in connection with the embodiments disclosed herein can be implemented or performed by a machine, such as a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. An image processing system can be or include a microprocessor, but in the alternative, the image processing system can be or include a controller, microcontroller, or state machine, combinations of the same, or the like configured to generate and analyze indicator feedback. An image processing system can include electrical circuitry configured to process computer-executable instructions. Although described herein primarily with respect to digital technology, an image processing system may also include primarily analog components. For example, some or all of the image file analysis and rotation notation features described herein may be implemented in analog circuitry or mixed analog and digital circuitry. A computing, environment can include a specialized computer system based on a microprocessor, a mainframe computer, a digital signal processor, a portable computing device, a device controller, or a computational engine within an appliance, to name a few.

The elements of a method, process, routine, or algorithm described in connection with the embodiments disclosed herein can be embodied directly in specifically tailored hardware, in a specialized software module executed by an image processing system, or in a combination of the two. A software module can reside in random access memory (RAM) memory, flash memory, read only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disk, a removable disk, a compact disc read-only memory (CD-ROM), or other form of a non-transitory computer-readable storage medium. An exemplary storage medium can be coupled to the image processing system such that the image processing system can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the image processing system. The image processing system and the storage medium can reside in an application specific integrated circuit (ASIC). The ASIC can reside in an access device or other monitoring device. In the alternative, the image processing system and the storage medium can reside as discrete components in an access device or other item processing device. In some embodiments, the method may be a computer-implemented method performed under the control of a computing device, such as an access device or other item processing device, executing specific computer-executable instructions.

As used herein, the term “selectively” or “selective” may encompass a wide variety of actions. For example, a “selective” process may include determining one option from multiple options A “selective” process may include one or more of: dynamically determined inputs, preconfigured inputs, or user-initiated inputs for making the determination. In some embodiments, an n-input switch may be included to provide selective functionality where n is the number of inputs used to make the selection.

As used herein, the terms “provide” or “providing” encompass a wide variety of actions. For example, “providing” may include storing a value in a location for subsequent retrieval, transmitting a value directly to the recipient, transmitting or storing a reference to a value, and the like. “Providing” may also include encoding, decoding, encrypting, decrypting, validating, verifying, and the like.

As used herein, the term “message” encompasses a wide variety of formats for communicating (e.g., transmitting or receiving) information A message may include a machine readable aggregation of information such as an XML document, fixed field message, comma separated message, or the like. A message may, in some embodiments, include a signal utilized to transmit one or more representations of the information. While recited in the singular, it will be understood that a message may be composed, transmitted, stored, received, etc. in multiple parts.