Abstract:
An image-based system and process of paper target scoring, and paper targets for use therewith, are disclosed. The system and process utilize functions that accumulate accuracy values based upon presumptions supplied to the present invention based upon the characteristics of bullet holes within paper target prior to any center point analysis. Subpixel analysis of images may heighten the accuracy of the scoring. The paper targets possess visual attributes adapted to permit scoring of the paper targets to be more rapid, facile, accurate, and secure.

Description:
FIELD OF THE INVENTION 
       [0001]    The present invention relates to the field of computer-aided measurement of apertures and more specifically to the field of measurement of projectile puncture dimensions in a target. 
       BACKGROUND 
       [0002]    The history of the shooting sports dates at least as far back to the 15th century when, in an effort to better organize a town&#39;s defenses, townspeople would gather periodically to practice their crossbowmenship skills. The process of scoring, assigning a value to each shot fired, has changed little in the last 500 years. Each competitor shoots a series of projectiles at an aiming mark. The score of each shot is typically represented with a numeric value, with the highest numeric values assigned to the shots closest to the center of the aiming mark. Human evaluation of each shot against the center of the aiming mark is the most widely used method for scoring. Pre-printed paper targets, with each aiming mark overlaid with a series of concentric circles facilitates the scoring process. However the scoring process is still manual. Visual Image Scoring is an invention to automate the scoring process for paper targets using commercially available image capture devices and computers. 
         [0003]    Manually scoring paper targets is slow, error prone, and open to human interpretation resulting in numerous problems. Human error may lead to the wrong value assigned to a shot, or the value of a series of shots may be added incorrectly. Furthermore two scorers may see the same shot on the same target and decided on two different values for that shot. This last problem is so pervasive that shooters describe scoring as “soft” or “hard,” terms that have come to describe scorers on the basis of whether they typically assign more or fewer points for similar shots. A major disadvantage arises when two scores fired by two shooters are compared. If the scorers do not use the same standards the comparison is less relevant. 
         [0004]    Another problem associated with scoring paper targets is the amount of time it takes to score each target and produce results. Even an experienced scorer needs 10 to 30 seconds per target (depending on the type of target) to score, inexperienced scorers need even longer (and sometimes their work has to be rechecked by an experienced scorer). Once scored the value of each shot needs to be manually transferred to a result list (typically a spreadsheet program). It is not uncommon for the wrong score to be assigned to the shooter, or for the score to be entered incorrectly. 
         [0005]    In a competition most rule books specify that a team of scorers must collectively score each paper target. This often leads to the statistic officer or match director to enlist volunteers. Additional personnel leads to additional costs for the match. 
         [0006]    The primary alternative to paper targets is electronic scoring targets (“ESTs”). EST systems do not use paper targets at all. Instead scoring is performed by acoustical or optical sensors. ESTs have demonstrated very quick results, reliability, and accuracy. However ESTs have a major flaw in that there is no demonstratable accuracy of each shot. Final results are based on trust that each EST performed correctly. 
         [0007]    A second, non-manual method of scoring exists for paper targets. These systems use proprietary scanners with built in scoring support. A host computer is used only for receiving the final scores. These systems measure only the radial distance from the center of the aiming circular mark to the center of the mark. These systems are designed to support only ISSF targets. Paper targets from all governing bodies come in many different shapes, sizes, number of aiming marks, scoring ring dimensions, and so on. 
         [0008]    Therefore, there is a need for a cost-effective but accurate scoring system that has demonstrable results for a generic type of target. Most shooting clubs and shooters have limited financial resources and cannot afford traditional ESTs, but they still have a need for an accurate scoring system. By leveraging commodity hardware the present invention can solve this problem. In addition, EST systems available today lack a self-contained mechanism to qualitatively demonstrate the accuracy of each projectile. A scoring system that can provide such demonstration would enhance the trustworthiness of scores in competitions. 
       SUMMARY 
       [0009]    The present invention is directed to a visual image scoring system, visual image scoring process, target sheet, and other affiliated devices and processes. The present invention is suited to measuring a high-velocity puncture in a substantially planar object quickly and accurately. The process includes disseminating planar target sheets derived from a predefined set of stored template target sheet images. The target sheet images bear a target with a space color and bull color, target sheet information, and reference data. A captured image of at least one of the target sheets having a high-velocity puncture is transmitted to an arithmetic logic unit (“ALU”). The captured image with the punctured target is then calibrated by comparing the captured image to reference data of the stored template that correlates to the captured target. The result of the calibration is correction data. 
         [0010]    Puncture edge data is extracted from the punctured target sheet that characterizes the periphery of at least two target punctures and also characterizes color data related to the puncture. A standard puncture dimension based on the captured image is calculated from the puncture data of at least two of the target punctures examined in the extraction step. A likely puncture center for a reviewed puncture is determined from the captured image. The determination is made as a function of the correction data, puncture edge data of the reviewed puncture, and a two-dimensional index of puncture accumulation values from the standard puncture dimension repeatedly overlayed as directed by the puncture edge data of the reviewed puncture. 
         [0011]    The target sheet of the present invention includes a substantially planar target sheet body with a view surface. A uniformly-colored space resides on the view surface and one or more circular bulls reside within the space. One or more bulls are uniformly filled with a single bull color. The target sheet further includes reference data on the body that includes a reference line and a predefined reference point. Further embodiments of the target sheet may include a target scheme identifier on the body to communicate to electronic reader information that identifies position data of said bull and reference data. 
         [0012]    A system of the present invention includes the ALU, persistent storage bearing a set of stored template target sheet images, a printer adapted to print a substantially planar target sheet from the set of stored template target sheet images, and a conventional, off-the-shelf (“COTS”) scanning device adapted to accept the target sheets. The system may further include: a transmitter function for transmitting a captured image of at least one target sheet with at least one high-velocity puncture to the ALU; a calibration function for calibrating the captured image of the punctured target sheet by comparing the captured image to the reference data of a correlating stored template target sheet image to produce correction data; an extraction function for extracting from the punctured target sheet puncture edge data characterizing color data related to the puncture and the periphery of at least two of the punctures; a calculator function for collecting from the captured image a standard puncture dimension based on the puncture edge data of at least two of the punctures; and a determination function for determining a likely puncture center point for a reviewed puncture from the captured image as a function of the correction data, puncture edge data from the reviewed puncture, and the 2-D index of puncture accumulation values from said standard puncture dimension repeatedly overlayed according to the puncture edge data of the reviewed puncture. 
         [0013]    Therefore, it is an aspect of the present invention to provide a cost-effective but accurate scoring system that has demonstrable results for a generic type of target. 
         [0014]    These aspects of the invention are not meant to be exclusive. Furthermore, some features may apply to certain versions of the invention, but not others. Other features, aspects, and advantages of the present invention will be readily apparent to those of ordinary skill in the art when read in conjunction with the following description, and accompanying drawings. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0015]      FIG. 1  is a view of the process of the present invention. 
           [0016]      FIG. 2  is a view of the target sheet of the present invention. 
           [0017]      FIG. 3  is a view of the process of the present invention. 
           [0018]      FIG. 4  is a view of the process of the present invention. 
           [0019]      FIG. 5  is a view of the process of the present invention. 
           [0020]      FIG. 6  is a view of the process of the present invention. 
           [0021]      FIG. 7  is a view of the process of the present invention. 
           [0022]      FIG. 8  is a view of the process of the present invention. 
           [0023]      FIG. 9  is a view of the process of the present invention. 
           [0024]      FIG. 10  is a view of the process of the present invention. 
           [0025]      FIG. 11  is a view of the process of the present invention. 
           [0026]      FIG. 12  is a view of the process of the present invention. 
           [0027]      FIG. 13  is a view of the process of the present invention. 
           [0028]      FIGS. 14A-C  are views of the process of the present invention. 
           [0029]      FIG. 15  is a view of the system of the present invention. 
           [0030]      FIG. 16  is a view of the system of the present invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0031]    Referring first to  FIG. 1 , a basic embodiment of the process  100  of measuring a high-velocity puncture in a substantially planar object is shown. The process  100  includes disseminating  102  planar target sheets derived from a set of predefined stored template target sheet images. The stored template target sheet images are an electronically-stored collection of one or more target sheet images. The template target sheet images are preferably stored in persistent memory. Different target sheet images within the set of stored template target sheet images contain different visual or informational attributes that may relate to identification, target arrangement, security, display, etc. 
         [0032]    As shown by  FIG. 2 , the target sheet images contain the information pertinent to create a target sheet  200 . The target sheet  200  includes a target section  204  with a space color and bull color, target sheet information, and reference data. The target sheets  200  are printed on paper and include two main sections: the target area  204  and information section  202 . The target section  204  includes a space  208  and a bull  206  (or “aiming mark”). The bull  206  is the natural aiming element for the shooter and the space  208  surrounds the bull  206  to provide visual contrast for the bull  206 . The target section  204  may have one or more bulls  206 .  FIG. 2  illustrates a target section  204  with only one aiming mark. The size and shape of the aiming mark is determined by the applicable national governing body rule book. Scoring rings may be printed on top of the aiming mark for the shooter&#39;s reference. For reasons that will be later discussed, it is preferred, but not necessary, to omit scoring rings from the bull  206 . 
         [0033]    Although  FIG. 2  shows the information section  202  as distinct from the target area  204 , these sections may overlap. The information section  202  may include a target serial number  222  and target scheme identifier  220 . Each target sheet  200  may be individually and uniquely numbered. Printed with each target number  222  is the target security code  210 . The target security code  210  may include any secured alphanumeric device, but is preferably derived from the target number  222 , a secret key, and a hashing or encrypting function—such as MD5. The target number  222  and the target security code  210  together create a secured target. Secure targets allow a match director to give a shooter a set of paper targets at the beginning of the match and then verify that the paper targets returned by the shooter are identical to the targets initially disseminated. 
         [0034]    The target scheme identifier  220  is shown in  FIG. 2  as a barcode. The target scheme identifier  220  permits the process  100  of the present invention to quickly and accurately identify the target scheme. By target scheme, it is meant the attributes of the target, including position and size data related to the bull  206 , position and size data related to the space  204 , position data related to informational elements  218 ,  216 ,  214 ,  210 ,  222 , and size and position date related to the reference data. The reference data preferably includes at least one reference line  212  and a reference point. Using barcodes as the scheme identifier mark is particularly useful since the technology is well known, proven, and readily available. Once the target scheme is known all other target element locations and dimensions may be looked up in a predetermined database such as the look up table of  FIG. 3 . For example, the target scheme may identify the first aiming bull to be 10.0 cm down and 4.0 cm to the right of the reference point. The reference point will be unique to each target and known based on the target scheme. It will be an easily identifiable location on the target, such as the left most point on the reference line  212 . 
         [0035]    The reference line  212  is used in conjunction with the reference point (the reference point and reference line may be correlated). The reference line  212  is used to measure the angle at which the target was captured. Although  FIG. 2  only shows a single reference line, multiple reference lines may be used as well. If a target sheet image was captured using a digital camera the multiple reference lines may be used by the process to correct for distortions in the camera lens. 
         [0036]    The target sheet  200  includes a competitor number box  216 . Competitors in a match may be given a unique competitor number. To correlate shooter to target the competitor number is written or pre-printed on the target sheet  200 . If written by hand or printed using characters the process may use existing optical character recognition (OCR) technology to identify the competitor. Other methods of preprinting the competitor number may also be used, such as bar codes. An event identifier  214  includes an event and series identification box. Similar to the competitor number box this information may be used to automatically determine which shot or series of shots the target represents in the match. The information may be pre-printed or filled in by the competitor. The target sheet  200  may include pre-printed text  218  that can be customized on a per-target basis. The text may contain, for example, the name of the match, the name of the shooter, or the name of the shooter&#39;s team. 
         [0037]    Returning to  FIG. 1 , after the target sheets are disseminated  102  to shooting participants, the targets will receive high-velocity punctures. The nature of the present invention is such that substantially circular punctures within, or depicted upon, a 2-dimensional object/array are required. The substantially circular punctures are formed by the high speeds of the projectiles used with the present invention. Suitable projectiles may include bullets, arrows with heads adapted to form circular apertures, and other projectiles with heads adapted to form substantially circular apertures. Substantially circular apertures include ellipses and other generally curved, continuous geometric entities. An image of the punctured target sheet is captured electronically and transmitted  104  to a processing unit, e.g. a computer, with an arithmetic logic unit (“ALU”). It is preferred that the image is captured with a conventional off-the-shelf (“COTS”) scanning device, digital camera, or other device adapted to electronically capture and transmit an image according to a machine readable language. Certain image capture devices are preferred over others for certain uses of the present invention. For example, a flat bed scanner, or a scanner with an automatic document feeder is preferred for 10 m air rifle targets because a scanner does not have nearly the lens distortion of a camera. Diminished distortion promotes more accurate analysis of the target sheet. Air rifle targets require the most accurate scoring of all current types of targets. On the opposite extreme, scoring a 600 yard rifle target necessitates a digital camera. The target&#39;s width is 72 inches and cannot fit upon any known COTS scanner. The best way to capture an image of such a target is to use a digital camera. 
         [0038]    The target image file used in the present invention may leverage existing image file formats such as JPEG or PNG. As is true with the image capture device, not all image file formats are preferred for the process  100 . For example to score air rifle targets, which requires the highest degree of accuracy, the image file should be lossless. A lossy file format adds side effects to the image that weaken the shot location algorithm&#39;s accuracy. The target image may either be stored on persistent media prior to substantial analysis, or the target image file may be passed directly into the ALU. 
         [0039]    The captured image with the punctured target is then calibrated  106  by comparing the captured image to reference data of the stored template that correlates to the captured target. In order to ascertain which of the stored templates corresponds to the captured target sheet image, the process  100  recognizes the target scheme, for example by visual recognition of the target scheme bar code. The target identification mark is preferably located near one of the four corners of the target sheet image. The four corners of the captured target sheet image are scanned in a search for the identification mark. Once found the mark can be read using existing computer vision technique and the corresponding target scheme of the stored target template set is determined. 
         [0040]    Once the target scheme is known, the dimensions of the target, the location of target elements, and all other information necessary to correctly identify and score the target may be looked up. The collective set of dimensions, location of elements, and additional information for scoring is known as the target scheme. The target scheme look up table (“LUT”), shown in  FIG. 3  item  300 , may be known a priori and stored on persistent media. Each known target scheme is listed in the “key” portion  314  of the look up table (example keys are items  302 ,  304 , and  306 ). The “value” portion  316  (example values are items  308 ,  310 , and  312 ), that contains the target dimensions and element locations, is read from the look up table and passed to the other stages of the process. A target scheme number that is not in the target scheme LUT results in an error. After the subject target sheet is determined, the reference data is utilized to determine correction data. 
         [0041]    Returning to  FIG. 1 , when images are captured they are rarely captured in such a way that horizontal and vertical lines match up exactly to the x and y direction of the image. In order to locate elements on the target image the process  100  needs to correct for any alignment errors during image capturing steps of the present invention. To properly calibrate  106 , the target scheme is used to identify the location of one or more reference lines. Once the general location of the reference line is known, based on the target scheme, existing computer vision techniques, e.g. Hough&#39;s Transform, may be used to locate the reference line&#39;s position and angle. As  FIG. 4  illustrates, an expected reference line  320  whose dimensions and position is gleaned from the set of stored template target sheets is compared with the found reference line  322 . From this information the error in the x direction, dx,  324 , error in the y direction, dy,  326 , and error in the angle, dθ,  328  may be calculated. The alignment process may also include corrections due to camera lens distortion. This again may be performed using the known reference lines and geometric camera calibration techniques. The calibrating process  106  may either create as calibrated data a new corrected target image or it may send the original target image with the dx, dy, dθ values to the later stages of the process  100 . 
         [0042]    Turning now to  FIGS. 5 and 6 , competitor identification  130  includes correlating a shooter with a target. Competitor identification is performed by locating the competitor number box  216 . Position data and dimensions of the competitor number box  216 , and other visual elements, is located within the target sheet image by knowing the location of the reference mark  226 . The location of the reference mark  226  is part of the target scheme definition, which is determined through identifying the target scheme through, for example, analysis of the target sheet bar code (not shown). The reference mark  226  may be any element that is visibly recognizable by a machine and has a location that is known or capable of being known to a reader. The difference between the reference marks expected and exact location is given by the calibration  106 . As an offset to the reference mark  226  the x distance  228  and y distance  230  to the competitor number box  216  is given by the target scheme. A competitor identification sub-image with x dimension  232  and y dimension  234  is extracted from the target sheet  200 . The x and y dimensions of the competitor number box  216  are provided by the target scheme as stored in persistent data. Depending on how the competitor number is printed, which may be specified in the target scheme, existing OCR, bar code reader, or similar computer vision techniques may be used to read and identify the competitor number. 
         [0043]    Turning now to  FIG. 7 , event and series identification  136  includes the means of determining which shot or series of shots the target represents. Event and series identification  136  is performed by locating the event and series box  236 . Position data and dimensions of the event and series box  236 , and other visual elements, are located within the target sheet  200  image by determining the location of the reference mark  226 . The location of the reference mark  226  is part of the target scheme definition, which is determined through identifying the target scheme through, for example, analysis of the target sheet bar code (not shown). The difference between the reference marks expected and exact location is given by the calibration  106 . As an offset to the reference mark  226  the x distance  228  and y distance  230  to the event and series box  236  is given by the target scheme. A competitor identification sub-image with x  232  and y  234  dimensions is extracted from the target sheet  200 . The x and y dimensions of the event and series box  236  are provided by the target scheme as stored in persistent data. Depending on how the competitor number is printed, which may be specified in the target scheme, existing OCR, bar code reader, or similar computer vision techniques may be used to read and identify the competitor number. 
         [0044]    Returning to  FIG. 5  with reference to  FIG. 8 , target authentication  134  is the means by which the match personnel can verify that the target sheet turned in by the shooter is the same target given to the shooter at the start of the match and begins with effective target sheet dissemination  102 . In order to authenticate  134  a target, the target is preferably marked with a unique number and hash code during the dissemination step. In the authentication means  134 , prior to the start of the match the match director may assign  802  a unique target number (or set of unique target numbers) to each shooter. The mapping between shooters and target numbers is recorded on persistent media  801 . The match director or another trusted individual creates a secret key  803 . Each target number is concatenated with the secret key  803 . The concatenated string is scrabbled  805  using a secure one way hashing function such as MD5. The result is a hashed string  804  that is stored back to the persistent media  801 . There is one hashed string for each target number. Both the target number  802  and corresponding hash code  804  are printed on the target  804  in a location that is known by the target scheme. The resulting targets are then distributed  807  out to the corresponding shooters at the start of the match. It is preferred that each target number is used only once. 
         [0045]    Turning now to  FIGS. 5 and 9 , once firing is complete for an event the shooters return the targets  905  to the match director. The target number and hash code may be read from the target  906 . The location of the target number and hash code is found in the calibration step  106 . The location is known by the target scheme, a sub-image can be extracted, and existing OCR or similar technique may read the target number and secure hash code. 
         [0046]    The read target number and hashed string from  906  is compared against the stored target number  802  retrieved from persistent media  801  in a comparison  907 . If the read value and stored value are not equal the shooter turned in a target other than the one the match director handed out at the start of the match. If the values are equal the target is authenticated  134 . 
         [0047]    Returning to  FIG. 1 , in shooting match scoring there are numerous parameters that are needed to correctly and quickly find the data of interest (e.g. the edge of the shot hole). These parameters such as the color of the shot hole and color of the aiming mark are known within small range of values. Variations in the digital image capture device, printing process of the paper target, and even the gun and ammo combination will cause errors in the expected parameter values. Unaccounted, these variations can cause havoc within the scoring algorithm. The extraction steps  110 ,  120  determine an appropriate set of parameters to use during the process  100  of the present invention. The extraction  110 ,  120  may be applied on each target for best accuracy (and slowest scoring speed) or to a set of targets where the process  100  is based on one target and the remaining targets are scored with the assumption that the parameters have not changed significantly, which in practice is generally true. 
         [0048]    There are five general parameters that need to be calculated per target sheet. The parameters include the color of the aiming mark, the color of the aiming white space, the color of the bullet hole, shot hole characteristics, and aiming mark characteristics. The characteristics of the shot hole and aiming mark are dependent on the type of shooting (e.g. air rifle or centerfire pistol), the type of target (identified by the target scheme), and the image capture device (e.g. scanner or digital camera). For example if air rifle targets are being analyzed, scanned in with a scanner, then only the average radius of the bullet hole and average radius of the aiming bull needs to be calculated  112 . The target scheme will offer the characteristics that need to be calculated. 
         [0049]    A paper target when digitized to an image has three general groups of colors, the aiming white space, the aiming mark, and the bullet hole. Identifying and differentiating between these three colors is important to the accuracy and speed of target scoring. The color of the aiming white space is generally ivory or white. The color of the aiming mark is generally black, although other colors may be used. The color of the bullet hole is dependent on the image capture device. Although often white or black, it may comprise virtually any color. 
         [0050]      FIG. 10  illustrates the extraction process  110 ,  120 . A representative target section  204  is used to determine the color values through histogram analysis  1002  and to determine  1003  the average bull and bullet hole dimensions. The resulting parameters, specifically the aiming black color  1005 , aiming white color  1006 , bullet hole color  1007 , aiming mark dimensions  1008 , and bullet hole dimensions  1009  are stored to persistent media  801  for use in the process  100  at a later time. 
         [0051]    The histogramming process  1002  is performed by selecting a representative sample of images from the target section  204 . An array of all possible colors is initialized to zero. The color of each pixel within the set of target images is taken. The array index corresponding to that color is incremented. This is repeated for all pixels in the image. The result is a histogram similar to that of  FIG. 11 . For demonstration purposes  FIG. 11  was taken from a gray scale image where the pixel color is a value between 0 and 255. There are three local maximums. The maximum closest to the expected aiming white color is the calculated color of the aiming white space  1006 . The local maximum closest to the expected aiming black color is the calculated color of the aiming bull black  1005 . The third local maximum, where ever it may lie, is the color of the shot holes  1007 . 
         [0052]    On most targets the aiming bull is a black circle filled in with multiple, concentric aiming lines. The size of the aiming mark is governed by applicable rule books, therefore the size should be known a priori. However due to variations in the target printing and the image capture phase the expected dimension may not be the actual dimensions. To calculate the dimension and to use it across multiple scoring runs the present invention utilizes an assumption: the dimension of the aiming bull as seen within a target sheet image is consistent across target sheet images taken with the same digital capture device and target printing lot. 
         [0053]    The present invention works ideally with an aiming bull that includes a uniform fill. That is to say, that only a single color is present within the bull. A bull free from aiming lines permits the present invention to operate with minimal complexity and obviates the need to account for line colors in the extraction steps of the present invention. In such embodiments where the aiming bull does include aiming lines, the present invention may account for the aiming lines by providing aiming lines of a known color distinct from the space color, bull color, and likely puncture color. In the alternative, the color of the aiming lines may match that of the space—which is usually white—and utilize reference data to predict position data related to the aiming marks and provide information to the present invention describing the expected amount of aiming line color per pixel of the captured image. 
         [0054]    Returning to  FIG. 1 , the aiming bull, or aiming mark, extraction  120  seeks to find the average dimension of the aiming mark as it appears on the target images. Existing computer vision geometric fitting techniques (e.g. Hough&#39;s transform) in conjunction with statistical sampling may be used to complete this task. A similar process may be used to find the characteristics of the shot holes. In practice though, the shot hole calibration process needs more samples than the bullet hole calibration process as shot holes tend to have significant tearing and irregular shapes, even in holes caused by high-velocity projectiles. To compensate for this extra noise multiple bullet hole samples are preferably utilized. However the basic means for extracting aiming mark data may be used to extract shot hole data. 
         [0055]    As with the assumption regarding the dimension of the aiming bull, a similar assumption about the bullet hole diameter is made. The bullet hole diameter is assumed to be constant across multiple shots on multiple targets. This assumption is generally true for the same gun and ammo combination. However the assumption breaks down across different gun and ammo combinations. A method to adjust  116 ,  126  for error inherent in the standardized dimension of the bull and shot hole is part of the present invention  100 . 
         [0056]    Hough&#39;s transform, the geometric fitting process used to find the center of the aiming bull and bullet holes during scoring is an O(x 3 ) problem. The calculating  112 ,  122  steps set one of the dimensions (namely the radius or diameter) to a fixed value. The calculating step is performed as the present invention uses visual recognition means to aggregate dimensions of multiple projectile holes and derive a standard dimension based on the aggregation. The aggregation may be based on two or more projectile holes. It is preferred that the standard dimension is simply the average of a known dimension value, e.g. radius, dimension, etc. However, any standard dimension that is based on the aggregation is part of the present invention and includes a standard dimension that is, e.g. 110%, 120%, 200%, or 300% of the aggregation average. Furthermore, the standard dimension may be the median of the aggregation values. It is preferred that the aggregation value, if, by way of example, includes the diameter, is equal to or greater than the average of the aggregation values, but no larger than three times the average of the aggregation values. However, the present invention includes all determinations of a standard dimension that is constantly applied across multiple reviewed projectile holes. Providing a standard dimension reduces the processes&#39; computational complexity to O(x 2 ). The complexity is in finding the x and y coordinates. This results in a significant speed up during scoring without compromising accuracy. Note that this discussion assumes the target image was captured using a scanner and has a circular aiming mark, if the target image was captured using a digital camera the fitting process may be a O(x 5 ) problem. However providing a standard dimension would still reduce complexity of the analysis, notwithstanding the use of the less accurate digital camera transmission, to find the x and y coordinates of each shot. 
         [0057]    Scoring  128  is the means of determining the center of the aiming mark and the center of each shot hole, comparing the difference, and looking up or calculating the score value of a shot. This process is further illustrated in  FIG. 12 . 
         [0058]    Each target section  204  is read and separated  1105  into a set of smaller single bull sub-images one per aiming bull  206 . The number and location of each aiming bull is provided by the target scheme. The single bull images  1201  are passed to the geometric fitting process  1107 . The output of the fitting process  1107  is the x and y location of the aiming mark and bullet holes (each sub-target may have zero, one, or more shots on it). Also as output is an accumulation value. It has been found that the accumulation value may be used as a measure of the shot&#39;s accuracy. The greater the value the more precisely the shot&#39;s location is known. 
         [0059]    Using the accumulation value as a metric for the accuracy of the shot location is an aspect of the present invention. Traditional paper targets scoring offers no quantifiable metric for a shot value&#39;s accuracy. A shot&#39;s score value is determined  128  based on the aiming mark location, bullet location, and the rules established by the governing bodies. These rules are passed into the scoring means  128  by the target scheme  1102 . Traditional paper targets have pre-printed scoring rings that determine the value of a shot. ESTs use an electrical center. In many ways calculating the center of the aiming mark is better than paper targets or ESTs. Paper targets (beyond human errors in scoring) suffer from inconsistent variations in the printing process and have been known to shrink or expand due to temperature and humidity. With ESTs, a shooter aims at a target or aiming mask and has to adjust his or her sights to the electrical center of the EST and not the center of the aiming mask. In practice the center of the aiming mask and the electrical center of the EST are very close. The danger associated with an EST is that the aiming mask moves during the competition, thus the shooter is no longer aiming and shooting at the electrical center of the target. With the present invention both the shooter and the scoring process use the exact same aiming mark. 
         [0060]    The details of the geometric fitting process  1107  are shown in  FIG. 13 . There are largely two parallel paths in the fitting process. One path to locate the center of the aiming mark, the second path to locate the center of the bullet hole. With the exception of input parameters these processes are nearly identical. 
         [0061]    A single aiming mark image  1201  is the input. The first step is segmentation  1204 . In this step each pixel in the image is categorized as either the reference color  1007  or “other.” This effectively creates a binary image  1205  showing only the bullet hole. The edge of the bullet hole is extracted  1206  using an edge detection algorithm. The resulting image  1207 , shows only the edge of the bullet hole. The bullet hole edge image  1207  is passed to the Hough transform process along with the expected bullet dimension previously determined in the extraction process  1003 . The result is a two dimensional array  1213  the same size as the original target image  1201  where each index value represents the possibility that a shot was centered there. As an adjustment step  1214 , the process finds the x and y index values above a predetermined threshold from the target scheme  1202 . These x and y index values represent a shot&#39;s location. The adjuster  1214  also uses statistical sampling from neighboring index values to achieve sub-pixel resolution. 
         [0062]    With reference to  FIGS. 1 and 13 , sub-pixel adjustment  116 ,  126  helps to account for quantization error during the image capture phase and more importantly compensates for using an average radius value for the bullet diameter (that was calculated for in the extraction steps  110 ,  120 . As discussed previously an assumption is made that all bullet diameters will be the same. This is a false assumption, but a practical one to find bullet holes in O(x 2 ) time. Sub-pixel resolution processing works very quickly and significantly reduces the error caused by the constant radius assumption. The x and y index is returned as the shot&#39;s location  1215 . In addition the index value is returned as the accumulation value  1215 . The accumulation value, which as discussed earlier, allows the present invention to give a quantifiable measure of each shot&#39;s accuracy. 
         [0063]    The process to locate the center of the aiming mark is nearly the same. Segmentation  1208  occurs between the color of the aiming mark and everything else. Edge detection  1210  detects the binary version of the aiming bull  1209  and the edge of the aiming mark  1211 . Hough transform is performed  1216  to generate a two dimensional accumulation array  1217 . Bull identification  1218  is slightly different since each image may only have one bull. Instead of finding any x and y index above a threshold, only the maximum index value is found. The index with the maximum value is the center of the aiming mark. A sub-pixel resolution  1218  determined through an adjustment function  1292  returns a value  1219  that is the x and y location of the bull and the index value as the accumulation 
         [0064]      FIGS. 14A-C  with reference to  FIG. 1 , depict the determining steps  114 ,  124  of the present invention. The adjustment function  1292  includes edge data related to the puncture hole  1406  arranged according to a 2-dimensional pixel array file  1402 . The standardized dimension  1408 , shown as a radius, is applied and a fit circle  1410  with a radius having the standard dimension is applied to each pixel  1404  that includes the puncture circle periphery  1406 . For each placement of the fit circle  1410 , each pixel within the fit circle receives a score. An accumulation array includes accumulation values bearing the sum of scores for each pixel. The pixel with the highest value in the accumulation array is the likely center of the puncture hole. The likely center is a very reliable estimate of the puncture center. The present step is used to determine the likely center of both the bull aiming mark and the bullet puncture. The achieve subpixel resolution, the process  100  of the present invention further includes adjustment  116 ,  126 . A weighted average of the surrounding pixels is taken to achieve an adjusted center. The adjusted center is highly accurate and surrounding pixel values may be included to proffer a reliability score for the center measurement. The adjustment function may operate along similar lines to determine more accurately a center based on an accumulation value for the bull location, and more particularly, the bull center. 
         [0065]    As  FIG. 15  shows, the system  1300  of the present invention includes a printing device  1306 , target sheet  200 , reproduction/transmission device  1302 , and processor device  1304  having an ALU and persistent memory. The system  1300  performs the process by accessing data within the persistent memory to send to the printing device  1306  data sufficient to generate target sheets  200  for dissemination. An image of the target sheet, subsequent to high-velocity puncturing, is transmitted to the ALU of the processor device  1304 , which may be identical or different from the processing device that printing the target sheets. The ALU performs the target sheet analysis steps of the present invention. 
         [0066]    The system  1300  includes a transmitter function for transmitting a captured image of at least one target sheet bearing at least one high-velocity puncture to the ALU, which performs the functions and other steps of the process of the present invention. A calibration function calibrates said captured image of said punctured target sheet by comparing the captured image to reference data of a correlating stored template target sheet image to produce correction data. An extraction function extracts from the punctured target sheet image puncture edge data characterizing the periphery of at least two of the punctures and color data related to the puncture. A calculator function collects from the captured image a standard puncture dimension based on the puncture edge data of at least two of the punctures. An identification function identifies a likely puncture center point for a reviewed puncture from the captured image as a function of said correction data, puncture edge data from the reviewed puncture, and a 2-D index of puncture accumulation values from the standard puncture dimension repeatedly overlayed according to said puncture edge data of said reviewed puncture. The system may further include an adjusting function for adjusting the likely puncture center point based on neighboring index values to produce an adjusted puncture center point. The system may further include a bull extraction function for extracting from the punctured target sheet bull edge data characterizing the periphery of at least two of the bulls and color data related to the bull; a bull calculator function for collecting from the captured image a standard bull dimension based on the bull edge data of at least two of the bulls; a bull identification function for identifying a likely bull center point of a reviewed bull as a function of the correction data, bull edge data from the reviewed bull, and a 2-D index of bull accumulation values from the standard bull dimension repeatedly overlayed according to the bull edge data; and a bull adjustment function for adjusting the likely bull center point based on neighboring bull index values to produce an adjusted bull center point. 
         [0067]    Turning now to  FIGS. 10 ,  13 , and  16 , the output of process  1107  may include a puncture overlay map  1500 . The puncture overlay map  1500  may include the x and y location and a reliability indicator  1506 , particularly a quantifiable reliability score, of the circular aiming bull and the bullet puncture. While the reliability score  1506  may be used to quantifiably measure the accuracy of the scoring process  100 , another method may be used to show qualitative accuracy to human operators. The image  1201  may be replicated to a new image. The ALU may then enhance the image by drawing a puncture overlay circle  1502  with the puncture diameter  1008 , known from the calibration values, with center at the computed x and y location value  1219  of the puncture hole. In similar fashion this image may again be enhanced by drawing a bull overlay circle  1504  with the aiming bull diameter  1008 , known from the calibration values, with center at the computed x and y location value  1215  of the aiming bull. The resulting image may be saved to persistent media or displayed to the human operator using existing graphical programs. The human operator may visually inspect and compare the computed puncture location with the puncture displayed in the graphic, as well as compare the computed bull location with the bull displayed in the graphic 
         [0068]    Although the present invention has been described in considerable detail with reference to certain preferred versions thereof, other versions would be readily apparent to those of ordinary skill in the art. Therefore, the spirit and scope of the appended claims should not be limited to the description of the preferred versions contained herein.