Patent Publication Number: US-2021192255-A1

Title: Reading system, reading method, storage medium, and moving body

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This is a continuation application of International Application PCT/JP2019/037257, filed on Sep. 24, 2019. This application also claims priority to Japanese Patent Application No. 2018-216046, filed on Nov. 16, 2018. The entire contents of each are incorporated herein by reference. 
    
    
     FIELD 
     Embodiments described herein relate generally to a reading system, a reading method, a storage medium, and a moving body. 
     BACKGROUND 
     There is a system that reads a character (e.g., a numeral) displayed in a segment display. It is desirable for the system to have high accuracy of reading the character. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram illustrating a configuration of a reading system according to a first embodiment; 
         FIGS. 2A to 2D  illustrate processing according to the reading system according to the first embodiment; 
         FIGS. 3A and 3B  illustrate processing according to the reading system according to the first embodiment; 
         FIG. 4  is a table illustrating the correspondence between the numerals and the combinations of the determination results; 
         FIGS. 5A to 5E  illustrate processing according to the reading system according to the first embodiment; 
         FIG. 6  is a flowchart illustrating processing according to the reading system  1  according to the first embodiment; 
         FIGS. 7A to 7D  are schematic views illustrating segment displays and setting of determination regions; 
         FIG. 8  is a block diagram illustrating a configuration of a reading system according to a first modification of the first embodiment; 
         FIG. 9  is a block diagram illustrating a configuration of a reading system according to a second modification of the first embodiment; 
         FIG. 10  is a block diagram illustrating a configuration of a reading system according to a second embodiment; 
         FIG. 11  is a block diagram illustrating a configuration of a reading system according to a third embodiment; 
         FIG. 12  is a schematic view describing an operation of the reading system according to the third embodiment; and 
         FIG. 13  is a block diagram illustrating a hardware configuration of the reading system according to the embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     According to one embodiment, a reading system includes a processing device. The processing device includes an extractor, a line thinner, a setter, and an identifier. The extractor extracts a partial image from an input image. A character of a segment display is imaged in the partial image. The segment display includes a plurality of segments. The line thinner thins a cluster of pixels representing a character in the partial image. The setter sets, in the partial image, a plurality of determination regions corresponding respectively to the plurality of segments. The identifier detects a number of pixels included in the thinned cluster for each of the plurality of determination regions, and identifies the character based on a detection result. 
     Various embodiments are described below with reference to the accompanying drawings. In the specification and drawings, components similar to those described previously in an antecedent drawing are marked with like reference numerals, and a detailed description is omitted as appropriate. 
     First Embodiment 
       FIG. 1  is a block diagram illustrating a configuration of a reading system according to a first embodiment. 
     The reading system according to the embodiment is used to read a character displayed in a segment display from an image in which the segment display is imaged. In the segment display, one character is displayed by multiple segments. The character is displayed by at least a portion of the multiple segments emitting light and by the remaining segments being unlit. The reading system according to the embodiment identifies the character from the image. 
     The number of segments included in the segment display to be read is arbitrary. For example, the segment display to be read may be a so-called seven-segment display in which one character is displayed by seven segments. The seven-segment display displays a character (a numeral) representing a number. A fourteen-segment display or a sixteen-segment display that displays an alphabet character may be the reading object. In the description herein, mainly, the reading system according to the embodiment reads a numeral displayed in a seven-segment display. 
     As illustrated in  FIG. 1 , the reading system  1  according to the first embodiment includes a processing device  10  and a memory device  20 . The processing device  10  includes, for example, an acceptor  11 , a pre-processor  12 , an extractor  13 , a line thinner  14 , a setter  15 , and an identifier  16 . 
       FIGS. 2A to 2D, 3A, 3B, and 5A to 5E  illustrate processing according to the reading system according to the first embodiment. 
       FIG. 4  is a table illustrating the correspondence between the numerals and the combinations of the determination results. 
     The processing according to the reading system according to the first embodiment will now be described with reference to  FIGS. 2A to 5E . 
     An image in which a segment display is imaged is input to the processing device  10 . The acceptor  11  accepts the input image. For example, an external imaging device generates the image by imaging the segment display. The imaging device transmits the image to the processing device  10 . Or, the image may be transmitted from an external memory device to the processing device  10 . The acceptor  11  accepts the image transmitted to the processing device  10 . An object other than a segment display may be imaged in the image. Herein, the image that is accepted by the acceptor  11  is called the input image. 
       FIG. 2A  is an example of an input image A transmitted to the processing device  10 . In the example of  FIG. 2A , multiple numerals are displayed by the segment display. Each of the numerals is displayed by multiple segments. 
     The pre-processor  12  applies preprocessing to the input image before identifying the numeral displayed by the segment display. The accuracy of the identification of the numeral can be increased by the preprocessing. For example, the pre-processor  12  includes a binarizer  12   a , an expansion processor  12   b , and a contraction processor  12   c.    
     The binarizer  12   a  binarizes the input image. The binarized input image is illustrated using two mutually-different colors (a first color and a second color). Here, a case will be described where the first color is white and the second color is black. 
     For example, the background of the segment display is a dark color. The segments that emit light are brighter than the background. Therefore, in the binarized input image, the segments that emit light are illustrated using white. The unlit segments and the background are illustrated using black. In other words, in the binarized input image, the numeral is shown by the white pixels. 
     Or, in a segment display in which a liquid crystal display is used, the character is illustrated using a color that is darker than the background. In such a case, inversion of the colors of the pixels is performed for the binarized input image. By inverting, the numeral is shown by the white pixels similarly to the case described above. Hereinafter, a case will be described where the segments that emit light are illustrated using white, and the background and the unlit segments are illustrated using black. 
     For example, the input image is digitized into data as an RGB color model shown using the three primary colors of red (Red), green (Green), and blue (Blue). In the binary processing, first, the input image is converted into data in HSV color space defined by the three components of hue (Hue), color saturation (Saturation), and luminance (Value). Then, a histogram analysis of the data in HSV color space is performed. Continuing, a threshold is calculated based on the histogram of the pixels. The pixels are binarized into white and black based on the threshold and the histogram of the pixels. 
     The expansion processor  12   b  expands the white pixels in the binary image. For example, the expansion processor  12   b  modifies the pixels adjacent to the white pixels to be white. Adjacent pixels that are white originally are not modified. For example, there are cases where black pixels are interspersed in portions where white pixels are clustered due to the effects of noise, etc. The expansion processing modifies the interspersed black pixels to be white pixels. Thereby, the effects of noise, etc., can be reduced, and the reading accuracy of the numeral can be increased. The expansion processing can connect clusters of proximate white pixels to each other. By connecting clusters of proximate white pixels to each other, one cluster of pixels that corresponds to one numeral is generated. The extraction of the partial image described below is made easy thereby. 
     The contraction processor  12   c  contracts the white pixels in the binary image. For example, the contraction processor  12   c  modifies pixels adjacent to black pixels to be black. Adjacent pixels that are black originally are not modified. The contraction processing reduces the number of expanded white pixels. 
       FIG. 2B  is an example of the input image A on which the preprocessing (the binarization, the expansion processing, and the contraction processing) has been performed. As illustrated in  FIG. 2B , clusters of white pixels corresponding to the numerals are generated by such preprocessing. 
     The pre-processor  12  may perform the expansion processing and the contraction processing described above multiple times. For example, the pre-processor  12  may perform the contraction processing two or more times after performing the expansion processing two or more times. The pre-processor  12  may perform the expansion processing two or more times after performing the contraction processing two or more times. For example, the implementation count of the expansion processing and the implementation count of the contraction processing may be set to be the same. Or, the implementation count of the expansion processing may be different from the implementation count of the contraction processing. For example, the implementation count of the expansion processing may be set to be more than the implementation count of the contraction processing. 
     The pre-processor  12  may perform a processing set including one expansion processing and one contraction processing multiple times. In one processing set, one of the expansion processing or the contraction processing is performed after the other is performed. The sequence of the expansion processing and the contraction processing in one processing set may be different from the sequence of the expansion processing and the contraction processing in another processing set. 
     The pre-processor  12  also may perform other processing. For example, when an object other than a segment display is included in the input image, the pre-processor  12  may cut out, from the input image, the portion in which the segment display is imaged. If the input image is distorted, the pre-processor  12  may perform a correction of the distortion. 
     The pre-processor  12  outputs the processed input image to the extractor  13 . The extractor  13  extracts a partial image from the input image. The partial image is a portion of the input image in which a numeral of the segment display is imaged. 
     For example, the extractor  13  includes a labeling processor  13   a  and a clipper  13   b . The binarized input image is output from the pre-processor  12  to the extractor  13 . The labeling processor  13   a  assigns a label (a value) to the cluster of white pixels. The “cluster of white pixels” refers to a portion in which white pixels are adjacent to each other and form one white clump. In the cluster of white pixels, one white pixel is adjacent to at least one white pixel. One cluster of white pixels corresponds to one numeral displayed by the segment display. When multiple clusters of white pixels exist, the labeling processor  13   a  assigns a label to each cluster of white pixels. 
     The clipper  13   b  cuts out the portion including the labeled cluster from the input image. The cut-out portion is used as the partial image. When multiple labeled clusters exist, the clipper  13   b  cuts out multiple partial images. The multiple partial images respectively include the multiple labeled clusters. For example, the partial image is rectangular. The partial image includes multiple pixels arranged in a first direction and in a second direction crossing the first direction. For example, the partial image is cut out so that the surface area (the number of pixels) is a minimum and each side contacts an outer edge of the cluster. 
       FIG. 2C  illustrates the input image A and partial images B 1  to B 4  cut out by the clipper  13   b . Each side of the partial images B 1  to B 4  contacts an outer edge of the cluster of white pixels. Therefore, the sizes of the partial images are different according to the sizes of the clusters. 
     The extractor  13  outputs the extracted (cut-out) partial image to the line thinner  14 . The line thinner  14  performs line thinning of the partial image. Namely, the line thinner  14  processes the cluster of white pixels included in the partial image to cause the line width to be one pixel. 
       FIG. 2D  illustrates the results of thinning the partial images B 1  to B 4  illustrated in  FIG. 2C . In the state of  FIG. 2C , the sides of the partial images contact the outer edges of the clusters of white pixels. Performing the thinning causes the sides of the partial images B 1  to B 4  to separate from the clusters of white pixels. 
     The line thinner  14  may thin the lines of the binary image output from the pre-processor  12 . For example, the clipper  13   b  stores the position where the partial image is to be cut out. The line thinner  14  outputs the thinned binary image to the extractor  13 . The clipper  13   b  cuts out a portion of the thinned binary image at the stored cut-out position. The thinned partial image illustrated in  FIG. 2D  is obtained thereby. 
     The setter  15  sets multiple determination regions in the thinned partial image. It is sufficient for the number of determination regions that are set to be not less than the number of segments used to display one character. For example, the number of determination regions that are set is equal to the number of segments used to display one numeral. For example, seven determination regions are set in one partial image when a numeral displayed by a seven-segment display is read. The positions of the determination regions are determined based on the size of the extracted partial image. For example, the memory device  20  stores information relating to the set positions of the determination regions. The setter  15  determines the positions of the determination regions based on the information stored in the memory device  20  and the size of the partial image. 
       FIG. 3A  is a schematic view for describing the method for setting the determination regions. A partial image C illustrated in  FIG. 3A  includes multiple pixels P. Determination regions DR 1  to DR 7  are set in the partial image C. The determination regions DR 1  and DR 2  are arranged along a first direction D 1 . The determination regions DR 3  and DR 4  are arranged along the first direction D 1 . The determination regions DR 1  and DR 2  are separated from the determination regions DR 3  and DR 4  in a second direction D 2 . The determination regions DR 5  to DR 7  are arranged along the second direction D 2 . 
     As in the determination regions DR 5  to DR 7  illustrated in  FIG. 3A , the arrangement direction of a portion of the determination regions may not be parallel to the second direction D 2  and may be tilted with respect to the second direction D 2 . For example, the angle between the second direction D 2  and the arrangement direction of a portion of the determination regions is set to be greater than 0 degrees and not more than 20 degrees. Similarly, the arrangement direction of another portion of the determination regions may be tilted with respect to the first direction D 1 . For example, the angle between the first direction D 1  and the arrangement direction of the other portion of the determination regions is set to be greater than 0 degrees and not more than 20 degrees. Such an arrangement also is included in the case where the multiple determination regions are arranged along the first direction D 1  or the second direction D 2 . 
     The length (the number of pixels) in the first direction D 1  of the partial image C illustrated in  FIG. 3A  is taken as L 1 . The length in the second direction D 2  of the partial image B is taken as L 2 . The partial image C includes first to fourth sides S 1  to S 4 . The first side S 1  and the second side S 2  are parallel to the first direction D 1 . The third side S 3  and the fourth side S 4  are parallel to the second direction D 2 . 
     For example, the setting of the determination regions DR 1  and DR 2  is referenced to a position separated L 2 / 4  from the first side S 1 . For example, the setting of the determination regions DR 3  and DR 4  is referenced to a position separated L 2 / 4  from the second side S 2 . For example, the setting of the determination regions DR 5  to DR 7  is referenced to the middle positions of the third and fourth sides S 3  and S 4 . For example, the determination regions DR 5  and DR 7  are set to positions shifted in the first direction D 1  from the middle positions. For example, the length in the second direction D 2  is set to L 2 / 3  for each of the determination regions DR 5  to DR 7 . Information that relates to the positions used as these references are stored in, for example, the memory device  20 . Each determination region is set so that the determination region does not overlap the other determination regions. Each determination region includes the pixel P at the position used as the reference, and the pixels P at the periphery of the pixel P. For example, the sizes of the determination regions are set according to the size of the partial image C. 
     The positions that are used as the references for setting the determination regions for the size of the partial image and the sizes of the determination regions for the size of the partial image are modifiable as appropriate according to the segment display to be read, the characteristics of the input image, etc. 
     Thus, the positions of the multiple determination regions are determined based on the size (the length in the first direction and the length in the second direction) of the partial image. The setter  15  outputs the determination regions that are set to the identifier  16 . 
     The identifier  16  identifies the numeral based on the number of pixels included in the thinned numeral in each determination region. For example, the identifier  16  includes a determiner  16   a  and a comparer  16   b.    
     The determiner  16   a  detects the number of pixels included in the thinned cluster in each determination region. When the segments that emit light are illustrated using white, the determiner  16   a  detects the number of white pixels in each determination region. The determiner  16   a  compares the detected number of pixels to a preset threshold and determines whether or not a portion of the numeral exists in each determination region. Specifically, the determiner  16   a  determines that a portion of the numeral exists in the determination region if the detected number of pixels is not less than the threshold. For example, the threshold is set to 1. 
     For example, the determiner  16   a  represents the determination result as “0” or “1” in each determination region. “0” indicates that a portion of the numeral does not exist in the determination region. “1” indicates that a portion of the numeral exists in the determination region. 
       FIG. 3B  is one of the multiple partial images illustrated in  FIG. 2D . As illustrated in  FIG. 3B , the determination regions DR 1  to DR 7  are set based on the size of the partial image B 2 . In the example of  FIG. 3B , portions of the numeral are determined to exist in the determination regions DR 2 , DR 3 , and DR 5  to DR 7 . For example, this result is represented as “0110111” using 0 and 1. 
     The comparer  16   b  refers to the memory device  20 . The correspondences between the numerals and the combinations of the determination results of each determination region are prestored in the memory device  20 .  FIG. 4  illustrates a table in which the correspondences are stored. The comparer  16   b  searches for a combination in the combinations of the determination results stored in the memory device  20  that matches the combination of the determination results of the determiner  16   a . The comparer  16   b  identifies, as the numeral shown in the partial image, the numeral that corresponds to the matching combination of the determination results. 
     For example, in the example of  FIG. 3B , the combination of the determination results is represented by “0110111”. The comparer  16   b  searches for a combination that matches this combination. As a result of the search, the combination of the determination results of the determiner  16   a  matches the combination of the determination results corresponding to the numeral “2”. Thereby, the comparer  16   b  identifies that the numeral shown in the partial image is “2”. 
     The form of the combination of the determination results is modifiable as appropriate as long as the combination of the determination results and the searched combinations are arranged according to the same rules. 
       FIGS. 5A to 5E  illustrate partial images showing other numerals and setting examples of the determination regions of the partial images. As illustrated in  FIGS. 5A to 5E , the positions and the sizes of the set regions are set according to the sizes of the partial images. 
     When multiple partial images are extracted by the extractor  13 , the setter  15  and the identifier  16  identify the set determination regions and identify the numerals for each of the partial images. The identifier  16  outputs the identified numerals. 
     For example, the processing device  10  outputs, to the external output device, information based on the numeral that is read. For example, the information includes the numeral that is read. The information may include a result calculated based on the numeral that is read. The processing device  10  may calculate another numeral based on multiple numerals that are read and may output the calculation result. The processing device  10  also may output information such as the time of the reading, etc. Or, the processing device  10  may output a file including the information such as the numeral that is read, the time of the reading, etc., in a prescribed format such as CSV, etc. The processing device  10  may transmit the data to an external server by using FTP (File Transfer Protocol), etc. Or, the processing device  10  may insert the data into an external database server by performing database communication and using ODBC (Open Database Connectivity), etc. 
     The processing device  10  includes, for example, a processing circuit made of a central processing unit. The memory device  20  includes, for example, at least one of a hard disk drive (HDD), a network-attached hard disk (NAS), an embedded multimedia card (eMMC), a solid-state drive (SSD), or a solid-state hybrid drive (SSHD). The processing device  10  and the memory device  20  are connected by a wired or wireless technique. Or, the processing device  10  and the memory device  20  may be connected to each other via a network. 
       FIG. 6  is a flowchart illustrating processing according to the reading system  1  according to the first embodiment. 
     The acceptor  11  accepts an input image transmitted to the processing device  10  (step St 11 ). The binarizer  12   a  binarizes the input image (step St 12   a ). The expansion processor  12   b  performs expansion processing of the binarized input image (step St 12   b ). The contraction processor  12   c  performs contraction processing of the binarized and expanded input image (step St 12   c ). The labeling processor  13   a  assigns a label to the cluster of white pixels included in the input image (step St 13   a ). The clipper  13   b  cuts out, from the input image, the partial image including the labeled cluster of white pixels (step St 13   b ). The line thinner  14  thins the cluster of white pixels in the input image or the partial image (step St 14 ). The setter  15  sets multiple determination regions in one partial image (step St 15 ). The determiner  16   a  detects the number of pixels included in the thinned cluster in each determination region. The determiner  16   a  determines whether or not a portion of a numeral exists in each determination region based on the number (step St 16   a ). The comparer  16   b  compares the combination of the determination results of the determiner  16   a  to a preregistered table (step St 16   b ). The comparer  16   b  sets the numeral included in the partial image to be the numeral corresponding to the combination of the determination results of the determiner  16   a.    
     Steps St 15  to St 16   b  are repeated until i is equal to the label count. In other words, initially, i is set to 0.1 is added to i when the identification of the numeral is completed for one cluster of white pixels. Steps St 15  to St 16   b  are repeated while i is less than the label count. Accordingly, when multiple labeled clusters of white pixels exist, the identification of the numeral is performed for each of the clusters. When the identification of the numeral is completed for all of the clusters, the numerals are output (step St 16   c ). 
     Effects of the first embodiment will now be described with reference to a reading method according to a reference example. 
     In the reading method according to the reference example, peaks of histograms along designated line segments are detected in an image in which the numeral of the segment display is imaged. Then, the numeral of the segment display is identified based on the numbers and the positions of the peaks. In the reading method, it is difficult to correctly detect the peaks when the boldness (the line width) of the numeral of the segment display is large. The positions of the peaks change according to the font of the numeral and the size of the image. It is difficult to correctly identify the numeral when the positions of the peaks are different from the positions used as the reference. 
     In the reading system  1  according to the first embodiment, line thinning is performed when reading the character displayed by the segment display. The cluster of pixels representing the character is thinned in the line thinning. Thereby, the width of the cluster of pixels representing the character can be uniform regardless of the boldness of the character of the segment display in the input image. Therefore, the character can be identified with high accuracy regardless of the boldness of the character of the segment display. 
     In the reading system  1  according to the first embodiment, multiple determination regions are set in the partial image in which the character of the segment display is imaged. The positions of the multiple determination regions are determined based on the size of the partial image. Then, the character of the segment display is identified based on the detection result of the number of pixels of the character in each of the multiple determination regions. By using the detection result of the number of pixels of the character, the character can be identified regardless of the font of the character. Also, by determining the positions of the multiple determination regions based on the size of the partial image, the character can be identified with high accuracy regardless of the size of the partial image. 
     In the reading system  1  according to the first embodiment, the line thinner  14  is optional. The character can be identified with higher accuracy by combining the line thinning of the line thinner  14  and the setting of the multiple determination regions based on the size of the partial image by the setter  15 . The line width of the cluster can be made uniform by thinning the cluster of pixels representing the character. The character can be identified with higher accuracy based on the determination result of the number of pixels regardless of the boldness of the character. 
       FIGS. 7A to 7D  are schematic views illustrating segment displays and setting of determination regions. 
     The reading system  1  according to the first embodiment is applicable also to segment displays other than a seven-segment display. For example, a character can be read by processing similar to the processing described above for a fourteen-segment display or a sixteen-segment display as well. 
       FIG. 7A  illustrates an example of a fourteen-segment display. In the fourteen-segment display, one character is displayed by fourteen segments. In such a case, the setter  15  sets fourteen or more determination regions in the partial image. For example, as illustrated in  FIG. 7B , the setter  15  sets fourteen determination regions DR in the partial image C. The memory device  20  stores a table of the correspondences between the characters and the determination results of the fourteen regions. The determiner  16   a  determines whether or not a portion of a character exists in each determination region DR. The comparer  16   b  refers to the table of the memory device  20  and searches for a numeral corresponding to the determination result. The character that is displayed by the fourteen-segment display is identified thereby. 
       FIG. 7C  illustrates an example of a sixteen-segment display. In the sixteen-segment display, one character is displayed by sixteen segments. In such a case, the setter  15  sets sixteen or more determination regions in the partial image. For example, the setter  15  sets sixteen determination regions DR in the partial image C as illustrated in  FIG. 7D . Thereafter, the character that is displayed by the sixteen-segment display is identified based on the determination result of the determiner  16   a  similarly to the example described above. 
     First Modification 
       FIG. 8  is a block diagram illustrating a configuration of a reading system according to a first modification of the first embodiment. 
     In the reading system  1   a  according to the first modification, the cutting out by the extractor  13  is performed before the preprocessing. For example, the cut-out position of the input image is prestored in the memory device  20 . The clipper  13   b  accesses the memory device  20  and refers to the stored cut-out position. The clipper  13   b  cuts out a portion of the input image at the cut-out position. The extractor  13  transmits, to the pre-processor  12 , the cut-out portion of the input image as the partial image. 
     In the pre-processor  12 , the partial image is binarized by the binarizer  12   a . The pre-processor  12  transmits the binarized input image to the line thinner  14 . Expansion processing and contraction processing of the binarized input image may be performed by the pre-processor  12 . 
     In the reading system  1   a  according to the first modification as well, the character that is displayed by the segment display can be read with higher accuracy. Labeling processing is unnecessary according to the reading system  1   a . If a cluster of white pixels representing one character is divided into two or more clusters when labeling processing is used to extract the partial images, the divided clusters are extracted as partial images. Accordingly, the numeral that is displayed by the segment display is not read correctly. When labeling processing is unnecessary, two or more divided clusters can be extracted as a partial image for identifying one character. 
     However, when a portion of the input image is cut out at a predetermined cut-out position, there is a possibility that a portion of the character may be cut off, or the character may be small in the partial image. Accordingly, it is desirable to extract the partial image by using labeling processing as illustrated in  FIG. 1  to increase the accuracy of the reading. 
     Second Modification 
       FIG. 9  is a block diagram illustrating a configuration of a reading system according to a second modification of the first embodiment. 
     In the reading system  1   b  according to the second modification, the pre-processor  12  includes a threshold calculator  12   d  and a pixel extractor  12   e . The threshold calculator  12   d  calculates thresholds based on the input image. For example, the memory device  20  stores a formula for calculating the thresholds. The threshold calculator  12   d  accesses the memory device  20  and refers to the formula. The threshold calculator  12   d  calculates adaptive thresholds. In other words, the threshold calculator  12   d  calculates a threshold for one pixel by using the formula and the brightness or the luminance of the pixel. The threshold calculator  12   d  calculates the thresholds of the pixels and transmits the thresholds to the pixel extractor  12   e.    
     The pixel extractor  12   e  compares the threshold and the brightness or the luminance of the pixel for each pixel included in the input image. For example, the pixel extractor  12   e  extracts only pixels of which the brightness or the luminance is not less than the threshold. Thereby, for example, only portions of lit segments are extracted. In other words, only pixels that represent a numeral are extracted. For example, the points where the pixels are not extracted are set to black. The pixel extractor  12   e  transmits the processed input image to the extractor  13 . 
     The extractor  13  and the subsequent components perform processing similar to those of the reading system  1  illustrated in  FIG. 1 . Or, the extractor  13  of the reading system  1   b  may perform processing similar to that of the extractor  13  of the reading system  1   a  illustrated in  FIG. 8 . 
     Second Embodiment 
       FIG. 10  is a block diagram illustrating a configuration of a reading system according to a second embodiment. 
     The reading system  2  according to the second embodiment further includes an imaging device  30 . The imaging device  30  generates an image by imaging a segment display. The imaging device  30  transmits the generated image to the processing device  10 . Or, the imaging device  30  may store the image in the memory device  20 . The processing device  10  accesses the memory device  20  and refers to the stored image. When the imaging device  30  acquires a video image, the imaging device  30  fetches a static image from the video image and transmits the static image to the processing device  10 . The imaging device  30  includes, for example, a camera. 
     The processing device  10  transmits, to an output device  40 , information based on characters that are identified and read. The output device  40  outputs the information received from the processing device  10  so that a user can recognize the information. The output device  40  includes, for example, at least one of a monitor, a printer, or a speaker. 
     For example, the processing device  10 , the memory device  20 , the imaging device  30 , and the output device  40  are connected to each other by a wired or wireless technique. Or, these devices may be connected to each other via a network. Or, at least two or more of the processing device  10 , the memory device  20 , the imaging device  30 , or the output device  40  may be embedded in one device. For example, the processing device  10  may be embedded in an integral body with the image processor of the imaging device  30 , etc. 
     Third Embodiment 
       FIG. 11  is a block diagram illustrating a configuration of a reading system according to a third embodiment. 
     The reading system  3  according to the third embodiment further includes a moving body  50 . The moving body  50  moves through a prescribed region. A segment display is provided inside the region through which the moving body  50  moves. The moving body  50  is, for example, an automated guided vehicle (AGV). The moving body  50  may be a flying object such as a drone, etc. The moving body  50  may be an independent walking robot. The moving body  50  may be an unmanned forklift, crane, or the like that performs a prescribed task. 
     For example, the processing device  10  and the imaging device  30  are mounted to the moving body  50 . The processing device  10  may be provided separately from the moving body  50  and may be connected to the moving body  50  via a network. When the moving body  50  moves to a position where the segment display is imageable, the imaging device  30  generates an image by imaging the segment display. 
     As illustrated in  FIG. 11 , the reading system  3  may further include an acquisition device  60 . The acquisition device  60  is mounted to the moving body  50 . For example, an identifier that includes unique identification information corresponding to the segment display is provided. The acquisition device  60  acquires the identification information of the identifier. 
     As illustrated in  FIG. 11 , the reading system  3  may further include a control device  70 . The control device  70  controls the moving body  50 . The moving body  50  moves through the prescribed region based on a command transmitted from the control device  70 . The control device  70  may be mounted to the moving body  50  or may be provided separately from the moving body  50 . The control device  70  includes, for example, a processing circuit made of a central processing unit. One processing circuit may function as both the processing device  10  and the control device  70 . 
     For example, the identifier is a radio frequency (RF) tag including ID information. The identifier emits an electromagnetic field or a radio wave including the ID information. The acquisition device  60  acquires the ID information by receiving the electromagnetic field or the radio wave emitted from the identifier. 
     Or, the identifier may be a one-dimensional or two-dimensional barcode. The acquisition device  60  may be a barcode reader. The acquisition device  60  acquires the identification information of the barcode by reading the barcode. 
     As illustrated in  FIG. 11 , the processing device  10  may further include an associator  17 . For example, when acquiring the identification information, the acquisition device  60  transmits the identification information to the processing device  10 . The associator  17  associates the transmitted identification information and the characters that are read and stores the associated information in the memory device  20 . 
       FIG. 12  is a schematic view describing an operation of the reading system according to the third embodiment. 
     For example, the moving body  50  is a moving body moving along a prescribed trajectory T. The imaging device  30  and the acquisition device  60  are mounted to the moving body  50 . The processing device  10  may be mounted to the moving body  50  or may be provided separately from the moving body  50 . The trajectory T is provided so that the moving body  50  passes in front of segment displays SD 1  and SD 2 . 
     For example, the moving body  50  moves along the trajectory T and decelerates or stops when arriving at a position where the segment display SD 1  or SD 2  is imageable by the imaging device  30 . For example, when decelerating or stopping, the moving body  50  transmits an imaging command to the imaging device  30 . Or, the imaging command may be transmitted to the imaging device  30  from the control device  70 . When receiving the command, the imaging device  30  images the segment display SD 1  or SD 2  while the moving body  50  has decelerated or stopped. 
     Or, the moving body  50  moves along the trajectory T at a speed such that the imaging device  30  can image the segment display SD 1  or SD 2  without blur. When the position where the segment display SD 1  or SD 2  is imageable by the imaging device  30  is reached, the imaging command is transmitted from the moving body  50  or the control device described above. When receiving the command, the imaging device  30  images the segment display SD 1  or SD 2 . When the image has been generated by imaging, the imaging device  30  transmits the image to the processing device  10  mounted to the moving body  50  or provided separately from the moving body  50 . 
     An identifier ID 1  is provided at the segment display SD 1  vicinity. An identifier ID 2  is provided at the segment display SD 2  vicinity. For example, the acquisition device  60  acquires the identification information of the identifier ID 1  or ID 2  while the moving body  50  has decelerated or stopped. 
     For example, the moving body  50  moves in front of the segment display SD 1 . The imaging device  30  generates an image by imaging the segment display SD 1 . The processing device  10  identifies the characters displayed by the segment display SD 1  from the image. The acquisition device  60  acquires the identification information of the identifier ID 1  corresponding to the segment display SD 1 . The processing device  10  associates the identification information and the identified characters. 
     Or, the acquisition device  60  may acquire the identification information of the identifier initially when the moving body  50  moves in front of the segment display. For example, a command to read the characters of a designated segment display is transmitted to the moving body  50 . The command includes information of the position of the segment display. The memory device  20  stores the identification information associated with the positions of the identifiers. The moving body  50  accesses the memory device  20  when the acquisition device  60  acquires the identification information. The moving body  50  refers to the position of the identifier associated with the identification information. The moving body  50  determines whether or not the position of the referred identifier matches the position of the segment display of the command to read the characters. In the case of a match, the moving body  50  uses the imaging device  30  to image the segment display SD 1 . In other words, in this method, the reading of the identification information functions as an interlock when reading the characters of the segment display. 
       FIG. 13  is a block diagram illustrating a hardware configuration of the reading system according to the embodiments. 
     For example, the processing device  10  of the reading systems  1 ,  1   a ,  1   b ,  2 , and  3  is a computer and includes ROM (Read Only Memory)  10   a , RAM (Random Access Memory)  10   b , a CPU (Central Processing Unit)  10   c , and a HDD (Hard Disk Drive)  10   d.    
     The ROM  10   a  stores programs controlling the operations of the computer. The ROM  10   a  stores programs necessary for causing the computer to function as the processing device  10 . 
     The RAM  10   b  functions as a memory region where the programs stored in the ROM  10   a  are loaded. The CPU  10   c  includes a processing circuit. The CPU  10   c  reads a control program stored in the ROM  10   a  and controls the operation of the computer according to the control program. The CPU  10   c  loads various data obtained by the operation of the computer into the RAM  10   b . The HDD  10   d  stores information necessary for reading and information obtained in the reading process. For example, the HDD  10   d  functions as the memory device  20  illustrated in  FIG. 1 . 
     Instead of the HDD  10   d , the processing device  10  may include an eMMC (embedded Multi Media Card), a SSD (Solid State Drive), a SSHD (Solid State Hybrid Drive), etc. 
     An input device  10   e  and an output device  10   f  may be connected to the processing device  10 . The user uses the input device  10   e  to input information to the processing device  10 . The input device  10   e  includes at least one of a mouse, a keyboard, a microphone (audio input), or a touchpad. Information that is transmitted from the processing device  10  is output to the output device  10   f . The output device  10   f  includes at least one of a monitor, a speaker, a printer, or a projector. A device such as a touch panel that functions as both the input device  10   e  and the output device  10   f  may be used. 
     A hardware configuration similar to  FIG. 13  is applicable also to the control device  70  of the reading system  3 . Or, one computer may function as the processing device  10  and the control device  70  in the reading system  3 . The processing and the functions of the processing device  10  and the control device  70  may be realized by collaboration between more computers. 
     The embodiments may include the following configurations. 
     Configuration 1 
     A reading system, comprising: 
     a processing device including
         an extractor extracting a partial image from an input image, a character of a segment display being imaged in the partial image, the segment display including a plurality of segments,   a setter setting, in the partial image, a plurality of determination regions corresponding respectively to the plurality of segments, positions of the plurality of determination regions being determined based on a size of the partial image, and   an identifier determining a number of pixels of a character for each of the plurality of determination regions and identifying the character based on a determination result.       

     Configuration 2 
     The reading system according to Configuration 1, wherein 
     the processing device further includes a pre-processor performing at least preprocessing of the input image, 
     the preprocessing includes binary processing of binarizing the input image into a first color and a second color, and 
     the extractor extracts, from the preprocessed input image, a portion including a cluster of pixels of the first color as the partial image. 
     Configuration 3 
     The reading system according to Configuration 2, wherein 
     the preprocessing further includes:
         processing in which a pixel adjacent to a pixel of the first color is modified into the first color in the input image; and   processing in which a pixel adjacent to a pixel of the second color is modified into the second color in the input image.       

     Configuration 4 
     The reading system according to any one of Configurations 1 to 3, wherein 
     the extractor extracts the partial image that is a rectangle made of a plurality of pixels arranged in a first direction and in a second direction crossing the first direction, and 
     the setter sets a portion of the plurality of determination regions to be arranged along the first direction and sets an other portion of the plurality of determination regions to be arranged along the second direction. 
     Configuration 5 
     The reading system according to Configuration 4, wherein 
     a number of the plurality of determination regions is equal to a number of segments used to display one character in the segment display. 
     Configuration 6 
     The reading system according to any one of Configurations 1 to 5, further comprising: 
     an imaging device generating the input image by imaging the segment display. 
     Configuration 7 
     The reading system according to any one of Configurations 1 to 6, wherein 
     the imaging device images a video image and cuts out, from the video image, the input image in which the segment display is imaged. 
     Configuration 8 
     The reading system according to Configuration 6 or 7, further comprising a moving body moving through a prescribed region and having the imaging device mounted to the moving body. 
     Configuration 9 
     The reading system according to Configuration 8, wherein 
     the moving body is an automated guided apparatus, a drone, or a robot. 
     Configuration 10 
     The reading system according to Configuration 8 or 9, wherein 
     the moving body decelerates or stops at a position where the segment display is imageable by the imaging device, and 
     the imaging device images the segment display while the moving body has decelerated or stopped. 
     Configuration 11 
     The reading system according to any one of Configurations 1 to 6, further comprising: 
     an acquirer acquiring identification information from an identifier including the identification information, the acquirer transmitting the identification information to the processing device, the identification information being unique, 
     the processing device further including an associator associating the identification information and the identified character. 
     Configuration 12 
     The reading system according to Configuration 11, further comprising: 
     a moving body moving through a prescribed region in which the segment display and the identifier are provided, and having the acquisition device mounted to the moving body. 
     Configuration 13 
     The reading system according to any one of Configurations 1 to 12, further comprising: 
     an output device, 
     the processing device transmitting, to the output device, information based on the identified and read character, 
     the output device outputting the information. 
     Configuration 14 
     A reading method, comprising: 
     extracting a partial image from an input image, a character of a segment display being imaged in the partial image, the segment display including a plurality of segments; 
     setting, in the partial image, a plurality of determination regions corresponding respectively to the plurality of segments, positions of the plurality of determination regions being determined based on a size of the partial image; and 
     determining a number of pixels of a character for each of the plurality of determination regions, and identifying the character based on a determination result. 
     Configuration 15 
     The reading method according to Configuration 14, further comprising: 
     causing a moving body to which an imaging device is mounted to move inside a region where the segment display is provided; and 
     acquiring the input image by the imaging device imaging the segment display. 
     Configuration 16 
     A storage medium storing a program causing a processing device to: 
     extract a partial image from an input image, a character of a segment display being imaged in the partial image, the segment display including a plurality of segments; 
     set, in the partial image, a plurality of determination regions corresponding respectively to the plurality of segments, positions of the plurality of determination regions being determined based on a size of the partial image; and 
     determine a number of pixels of a character for each of the plurality of determination regions, and identify the character based on a determination result. 
     Configuration 17 
     A moving body moving through a prescribed region where a segment display including a plurality of segments is provided, the moving body having an imaging device mounted to the moving body, the moving body comprising: 
     a processing device receiving an input of an image of the segment display imaged by the imaging device, 
     the processing device including
         an extractor extracting a partial image from the input image, a character of the segment display being imaged in the partial image, the segment display including a plurality of segments,   a setter setting, in the partial image, a plurality of determination regions corresponding respectively to the plurality of segments, positions of the plurality of determination regions being determined based on a size of the partial image, and   an identifier determining a number of pixels of a character for each of the plurality of determination regions, and identifying the character based on a determination result.       

     Configuration 18 
     The moving body according to Configuration 17, further comprising: 
     a control device controlling the moving body and the imaging device, 
     the control device causing the imaging device to image the segment display when the moving body moves to a position where the segment display is imageable by the imaging device. 
     By using the reading system, the reading method, and the moving body according to the embodiments described above, the numerals displayed by the segment display can be read with higher accuracy. Similarly, by using a program for causing a computer to operate as the reading system, the numerals displayed by the segment display can be read by the computer with higher accuracy. 
     For example, the processing of the various data recited above is executed based on a program (software). For example, the processing of the various information recited above is performed by a computer storing the program and reading the program. 
     The processing of the various information recited above may be recorded in a magnetic disk (a flexible disk, a hard disk, etc.), an optical disk (CD-ROM, CD-R, CD-RW, DVD-ROM, DVD±R, DVD±RW, etc.), semiconductor memory, or another recording medium as a program that can be executed by a computer. 
     For example, the information that is recorded in the recording medium can be read by a computer (or an embedded system). The recording format (the storage format) of the recording medium is arbitrary. For example, the computer reads the program from the recording medium and causes a CPU to execute the instructions recited in the program based on the program. The acquisition (or the reading) of the program by the computer may be performed via a network. 
     The processing device and the control device according to the embodiments include one or multiple devices (e.g., personal computers, etc.). The processing device and the control device according to the embodiments may include multiple devices connected by a network. 
     While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel embodiments described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the embodiments described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the invention. The above embodiments can be practiced in combination with each other.