WO2014129016A1 - Dispositif de reconnaissance de caractères, procédé de reconnaissance de caractères et support d'enregistrement - Google Patents

Dispositif de reconnaissance de caractères, procédé de reconnaissance de caractères et support d'enregistrement Download PDF

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Publication number
WO2014129016A1
WO2014129016A1 PCT/JP2013/079119 JP2013079119W WO2014129016A1 WO 2014129016 A1 WO2014129016 A1 WO 2014129016A1 JP 2013079119 W JP2013079119 W JP 2013079119W WO 2014129016 A1 WO2014129016 A1 WO 2014129016A1
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Prior art keywords
character
character recognition
evaluation value
recognition result
recognition
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PCT/JP2013/079119
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English (en)
Japanese (ja)
Inventor
洋平 小島
斎藤　真由美
杉本　喜一
拓馬 岡▲崎▼
健太 中尾
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三菱重工業株式会社
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Priority to SG11201506566YA priority Critical patent/SG11201506566YA/en
Publication of WO2014129016A1 publication Critical patent/WO2014129016A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10—Character recognition
    • G06V30/14—Image acquisition
    • G06V30/148—Segmentation of character regions
    • G06V30/158—Segmentation of character regions using character size, text spacings or pitch estimation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10—Character recognition

Definitions

  • the present invention relates to a character recognition device, a character recognition method, and a recording medium, and more particularly, to a character recognition device, a character recognition method, and a recording medium for performing character recognition on a grayscale image.
  • the technology for performing character recognition on a captured image captured by an imaging apparatus is applied to various uses including license plate recognition.
  • character recognition for a captured image generally, processing for generating a binarized image from the captured image is performed, and character recognition processing is further performed for the binarized image.
  • Such a technique is disclosed in, for example, Japanese Patent Application Laid-Open No. 2006-338578.
  • One problem with the technique of generating a binarized image from a captured image and performing character recognition processing on the binarized image is that a good binarized image cannot be obtained if the image quality of the captured image is poor. is there.
  • imaging with low light quantity and low resolution is performed in accordance with the cost reduction of the imaging apparatus.
  • the amount of light decreases, shadows occur, and the luminance distribution becomes non-uniform as the S / N ratio decreases.
  • the resolution is lowered, the character feature amount in the captured image is deteriorated.
  • Patent Document 2 Japanese Patent Laid-Open No. 2008-251029
  • Non-Patent Document 1 Korean Patent Laid-Open No. 2008-251029
  • Patent Document 2 discloses a technique for improving character recognition accuracy by obtaining a high-resolution image by a super-resolution processing method in character recognition processing.
  • Non-Patent Document 1 discloses a technique for identifying a character class by statistical pattern recognition using a feature quantity such as a luminance gradient obtained from a grayscale image.
  • an object of the present invention is to provide a technique for simultaneously improving the accuracy of character recognition and reducing the amount of calculation in character recognition processing for a grayscale image.
  • a character recognition device that performs character recognition on a grayscale image in which a character string composed of characters arranged in a specific direction is displayed.
  • Character recognition apparatus among the strings, N C-number from the first end (N C is 2 or more predetermined value) for the first character is a character of the first character recognition means for performing character recognition, the character string And second character recognition means for performing character recognition on a second character which is a character other than N C characters from the first end.
  • the first character recognition means sets a plurality of first character regions having various character region sizes at respective positions in the gray scale image, and performs character recognition for each of the plurality of first character regions.
  • Processing is performed to calculate a character recognition result and an evaluation value, and based on the calculated evaluation value, a character recognition result of the first character and a first optimum character area size that is an optimum character area size are determined.
  • the second character recognition means sets a plurality of second character areas having the first optimum character area size at each position of the gray scale image, performs character recognition processing for each of the plurality of second character areas, and performs a character recognition result.
  • the evaluation value, and the character recognition result of the second character is determined based on the character recognition result and the evaluation value calculated for each of the plurality of second character regions.
  • the first character recognizing means determines each character position of the first character based on the evaluation value, determines an optimal character size that is an optimal character spacing from the determined character position,
  • the two-character recognition means preferably sets the positions of the plurality of second character areas according to the optimum inter-character size.
  • the first character recognition unit ranks the character recognition results obtained for each position of the plurality of first character regions based on the evaluation value.
  • First character recognition means for each character area size, ranking a character recognition results obtained for each position of the plurality of first character region has a higher evaluation value from among the character recognition result is one of m C 1 (m C is a predetermined number greater than N C ) is extracted, and a first average value that is an average value of evaluation values of m C character recognition results is calculated. It is preferable to determine the character region size having the highest average value as the optimum character region size.
  • the first character recognizing means includes pixels having luminance values corresponding to the evaluation values of m C character recognition results, corresponding to the m C character recognition results.
  • An evaluation value-luminance value conversion plot image which is an image located at a region position, is generated and a binarization process is performed on the evaluation value-luminance value conversion plot image to generate a binarized image. preferable.
  • the first character recognition means performs a labeling process on the binarized image to give a label to each set of continuous pixels having the same color, and for each label, character recognition corresponding to a pixel belonging to the label A second average value that is an average value of the evaluation values of the results is calculated, and the first character recognizing unit sequentially calculates the centroid position of each label and the centroid position of other labels in order from the label having the second highest average value.
  • the process of removing each label is repeated until N C labels are left when the distance between the labels is calculated and the center of gravity has a center of gravity such that the distance from the center of gravity of another label is equal to or less than a predetermined threshold. Do.
  • the first character recognition means selects a pixel having the highest evaluation value of the corresponding character recognition result from among the pixels belonging to each of the remaining N C labels, The position is determined as the character position of the first character, and the optimal inter-character size, which is the optimal character spacing, is determined from the determined character position.
  • the second character recognition means sets the positions of the plurality of second character areas according to the optimum inter-character size.
  • the character recognition device further includes third character recognition means for performing character recognition on a third character that is N C characters from the second end opposite to the first end in the character string; A fourth character recognition unit that performs character recognition on a fourth character that is a character other than N C characters from the second end of the character string, and a final character recognition result determination unit may be included.
  • the third character recognition means sets a plurality of third character areas having various character area sizes at respective positions in the gray scale image, and performs character recognition for each of the plurality of third character areas.
  • Processing is performed to calculate a character recognition result and an evaluation value, and based on the calculated evaluation value, a character recognition result for the third character and a second optimum character area size that is an optimum character area size are determined.
  • the fourth character recognition means sets each position of the gray scale image of the plurality of fourth character areas having the second optimum character area size, performs character recognition processing for each of the plurality of fourth character areas, and performs a character recognition result.
  • the evaluation value, and the character recognition result of the fourth character is determined based on the calculated evaluation value.
  • the final character recognition result determining means is a method in which the character recognition result of the specific character of the character string obtained by the first character recognition means and the second character recognition means is obtained by the third character recognition means and the fourth character recognition means.
  • the matching character recognition result is determined as the final character recognition result of the specific character. If they do not match, the final character recognition result determination means is obtained by the character recognition result of the specific character obtained by the first character recognition means and the second character recognition means, and by the third character recognition means and the fourth character recognition means. The character recognition result having the higher evaluation value among the character recognition results of the specific character is determined as the final character recognition result of the specific character.
  • the first character recognition means includes storage means for storing similar character data in which similar characters are registered, and a character recognition result obtained by performing character recognition processing for each of the plurality of first character areas.
  • the optimum character area size is determined without using the character recognition result matching the similar character and its evaluation value.
  • a character recognition device that performs character recognition on a grayscale image on which a character string composed of characters arranged in a specific direction is displayed.
  • the character recognition apparatus in the character string, N C-number (N C is 2 or more predetermined value) from the end and the first character recognition means for performing character recognition for the first character is a character, an end character string To a second character recognition means for performing character recognition on the second character which is a character other than N C characters.
  • the first character recognition means sets a plurality of first character regions having various character region sizes at respective positions in the gray scale image, and performs character recognition for each of the plurality of first character regions.
  • a character recognition result and an evaluation value are calculated by performing processing, and the character recognition result of the first character and each character position of the first character are determined based on the calculated evaluation value, and the determined character position To determine the optimum character spacing, which is the optimum character spacing.
  • the second character recognition means sets a plurality of second character areas at each position of the grayscale image according to the optimum inter-character size, performs character recognition processing for each of the plurality of second character areas, The evaluation value is calculated, and the character recognition result of the second character is determined based on the character recognition result and the evaluation value calculated for each of the plurality of second character regions.
  • a character recognition method for performing character recognition on a grayscale image in which a character string composed of characters arranged in a specific direction is displayed.
  • the character recognition method in the character string, N C-number (N C is 2 or more predetermined value) from the end and performing character recognition for the first character is a character of, N C-number from the end of the string Recognizing a second character that is not a character.
  • N C-number N C is 2 or more predetermined value
  • performing character recognition for the first character is a character of, N C-number from the end of the string Recognizing a second character that is not a character.
  • a plurality of first character regions having various character region sizes are set at respective positions in the gray scale image, and character recognition processing is performed for each of the plurality of first character regions.
  • a result and an evaluation value are calculated, and based on the calculated evaluation value, a character recognition result of the first character and a first optimum character area size which is an optimum character area size are determined.
  • a character recognition result of the first character and a first optimum character area size which is an optimum character area size are determined.
  • a plurality of second character areas having a first optimum character area size are set at each position of the grayscale image, and character recognition processing is performed for each of the plurality of second character areas.
  • the character recognition result and the evaluation value are calculated, and the character recognition result of the second character is determined based on the character recognition result and the evaluation value calculated for each of the plurality of second character areas.
  • a character recognition method for performing character recognition on a grayscale image in which a character string composed of characters arranged in a specific direction is displayed.
  • the character recognition method in the character string, N C-number (N C is 2 or more predetermined value) from the end and performing character recognition for the first character is a character of, N C-number from the end of the string Recognizing a second character that is not a character.
  • N C-number N C is 2 or more predetermined value
  • Character recognition processing and an evaluation value are calculated with respect to the character recognition result, and the character recognition result of the first character and each character position of the first character are determined and determined based on the calculated evaluation value.
  • the optimum character spacing which is the optimum character spacing, is determined from the determined character position.
  • a plurality of second character areas are set at respective positions in the grayscale image in accordance with the optimum inter-character size, and character recognition processing is performed for each of the plurality of second character areas.
  • the recognition result and the evaluation value are calculated, and the character recognition result of the second character is determined based on the character recognition result and the evaluation value calculated for each of the plurality of second character areas.
  • a recording medium for recording a program that causes a computing device to perform character recognition on a grayscale image on which a character string composed of characters arranged in a specific direction is displayed.
  • the program includes a step of performing character recognition for the first character that is N C characters (N C is a predetermined value of 2 or more) from the end of the character string, and other than N C characters from the end of the character string. And causing the arithmetic unit to execute character recognition for the second character, which is a character.
  • character recognition for the first character a plurality of first character regions having various character region sizes are set at respective positions in the gray scale image, and character recognition processing is performed for each of the plurality of first character regions. A result and an evaluation value are calculated, and based on the calculated evaluation value, a character recognition result of the first character and a first optimum character area size which is an optimum character area size are determined.
  • character recognition for the second character a plurality of second character areas having a first optimum character area size are set at each position of the grayscale image, and character recognition processing is performed for each of the plurality of second character areas. The character recognition result and the evaluation value are calculated, and the character recognition result of the second character is determined based on the character recognition result and the evaluation value calculated for each of the plurality of second character areas.
  • a recording medium for recording a program that causes a computing device to perform character recognition on a grayscale image on which a character string composed of characters arranged in a specific direction is displayed.
  • the program includes a step of performing character recognition for the first character that is N C characters (N C is a predetermined value of 2 or more) from the end of the character string, and other than N C characters from the end of the character string. And causing the arithmetic unit to execute character recognition for the second character, which is a character.
  • character recognition for the first character in character recognition for the first character, a plurality of first character areas of various character area sizes are set at respective positions in the grayscale image, and each of the plurality of first character areas is set. Character recognition processing and an evaluation value are calculated with respect to the character recognition result, and the character recognition result of the first character and each character position of the first character are determined and determined based on the calculated evaluation value. The optimum character spacing, which is the optimum character spacing, is determined from the determined character position.
  • character recognition for the second character a plurality of second character areas are set at respective positions in the grayscale image in accordance with the optimum inter-character size, and character recognition processing is performed for each of the plurality of second character areas. The recognition result and the evaluation value are calculated, and the character recognition result of the second character is determined based on the character recognition result and the evaluation value calculated for each of the plurality of second character areas.
  • FIG. 1 is a block diagram showing a configuration of a character recognition device 1 according to an embodiment of the present invention.
  • the character recognition device 1 is used for license plate recognition.
  • the character recognition device 1 performs character recognition processing on the plate area image data 21 supplied from the outside to generate plate recognition data 22.
  • the plate area image data 21 is image data of a plate area image, that is, an image in which a license plate (automobile registration number mark or vehicle number mark) is projected. For example, from a captured image obtained by photographing a vehicle, It is obtained by image processing that cuts out a portion corresponding to the license plate.
  • the plate area image data 21 is grayscale image data.
  • the plate recognition data 22 is data indicating a character recognition result (that is, a recognized character) obtained by the character recognition process.
  • the character recognition device 1 includes an image processing IC (integrated circuit) 2, an external interface 3, an external storage device 4, a memory 5, and a ROM (read only memory) 6.
  • the external interface 3 supplies the plate area image data 21 received from the outside to the image processing IC 2.
  • the external storage device 4 stores data generated in the character recognition process in the character recognition device 1.
  • Data stored in the external storage device 4 includes plate recognition data 22.
  • the memory 5 is used as a working area for arithmetic processing by the image processing IC 2.
  • the ROM 6 stores a program executed by the image processing IC 2.
  • the program stored in the ROM 6 includes character recognition software 6a that is a program for executing character recognition processing.
  • the recording medium for recording the character recognition software 6a may be used for installing the character recognition software 6a in the ROM 6.
  • the character recognition software 6a may be stored in the external storage device 4.
  • a recording medium for recording the character recognition software 6a may be used for installing the character recognition software 6a in the external storage device 4.
  • the image processing IC 2 includes an arithmetic module 11, an image input interface 12, a data input / output interface 13, a memory controller 14, and a ROM controller 15.
  • the arithmetic module 11, the image input interface 12, the data input / output interface 13, the memory controller 14, and the ROM controller 15 are connected by an internal bus 16.
  • the arithmetic module 11 executes the character recognition software 6 a while using the memory 5 as a working area, and performs character recognition processing on the plate area image data 21.
  • the image input interface 12 is an interface used for inputting the plate area image data 21 to the image processing IC 2.
  • the data input / output interface 13 is an interface for accessing the external storage device 4.
  • the memory controller 14 is an interface for accessing the memory 5.
  • the ROM controller 15 is an interface for accessing the ROM 6.
  • FIG. 2 illustrates an example of an image of plate area image data 21 on which character recognition processing is performed in the character recognition method of the present embodiment, that is, an example of a plate area image.
  • the plate region image is a grayscale image, and is obtained by cutting out a portion corresponding to a license plate from a vehicle captured image obtained by photographing a vehicle.
  • description will be made using the xy coordinate system defined for the plate region image.
  • the x axis is defined in the character width direction (horizontal direction) of the plate area image
  • the y axis is defined in the character height direction (vertical direction) of the plate area image.
  • the character recognition method of the present embodiment is based on the premise that the size of each character is substantially the same in the plate area image. Such a premise is appropriate for license plate recognition, for example.
  • FIG. 3 is a flowchart showing an outline of the character recognition method in this embodiment.
  • the character recognition software 6a described above is a program code group for executing this character recognition method.
  • step S01 character recognition processing is performed for N C characters from one end (step S01).
  • N C is the designated number of characters.
  • the plate area image in FIG. 2 shows an example in which character recognition processing is performed on the leftmost three characters in step S01.
  • the character area is an area where each character is considered to exist.
  • FIG. 4 is a diagram showing an example of a character area.
  • the character area 31 is a rectangle (that is, a rectangle (including a square)), and the position of each character area 31 is the center of the character area 31. That is, it is defined as the intersection 33 of the diagonal lines 32.
  • the optimum character recognition result ie, the recognized character
  • the optimum position and size of the character region are searched.
  • step S02 information on the size of the character region and the character spacing obtained by the character recognition process in step S01 is used.
  • the character recognition method of the present embodiment reduces the search range in the character recognition process in step S02 by such a method, and simultaneously improves the accuracy of character recognition and reduces the amount of calculation.
  • the process in each step will be described in detail.
  • FIG. 5 is a flowchart showing details of the character recognition processing for N C characters in step S01.
  • step S01 generally, after initial setting (step S11), character areas of various sizes are set at various positions, and character recognition processing is performed for each of the set character areas. (Steps S12 to S15). Further, based on the evaluation value calculated in the character recognition process, the optimum character area size, character position, character spacing (character spacing), and optimum character recognition result are determined (steps S16 to S18).
  • the character recognition process for N C characters in step S01 will be described in detail.
  • the character area initial size is the size of the character area initially set.
  • the size of the character area in the x direction that is, the width of the character area
  • the size in the y direction that is, the height of the character area.
  • the character area size increment is an increment when the size of the character area is changed in the search for the optimum character area, and includes an x-direction increment and a y-direction increment.
  • the maximum character area size is the maximum size when changing the size of the character area in the search for the optimal character area, and includes the maximum value in the x direction and the maximum value in the y direction.
  • the shift amount of the character area is a designated value of the change amount of the character area when the position of the character area is changed in the search for the optimum character area, and includes the x-direction shift amount and the y-direction shift amount. .
  • step S12 the size of the character area is set (step S12).
  • the size of the character area is set to the character area initial size defined as the initial setting.
  • a size obtained by changing the initial size of the character region in accordance with the x-direction increment and the y-direction increment is selected as the size of the character region.
  • the size of the character area set in step S12 is hereinafter referred to as area size #k. k is an index representing the region size.
  • the position of the character area is set (step S13).
  • the position set in step S13 is referred to as a region position (i, j).
  • i is an index representing a position in the x-axis direction
  • j is an index representing a position in the y-axis direction.
  • the character area is rectangular, and the position of the character area is defined as the center of the character area.
  • the position of the character area is set to a predetermined process start position.
  • the processing start position is the range of the assumed position. It may be determined appropriately according to the situation.
  • the position of the character area is set by changing the position of the character area in accordance with the shift amount of the character area included in the initial setting.
  • a character recognition process is performed for the character region whose position is determined in step S13 (step S14).
  • the position of the character area is determined to be the area position (i, j) in step S13
  • the character recognition result in the character area at the area position (i, j) in the character recognition process in step S14 (that is, recognized) Character) and its evaluation value.
  • the character recognition results for the character region at the region position (i, j) are ranked based on the evaluation value.
  • an algorithm as disclosed in Non-Patent Document 1 described above may be used.
  • FIG. 6 is a diagram showing a specific example of the character recognition process in step S14.
  • the character “S” with an evaluation value of 0.911 is obtained as the first character recognition result
  • the evaluation value is The character “2” which is 0.566 is obtained as the second character recognition result.
  • the evaluation value is a value in the range of 0 to 1.0, and it is assumed that the higher the matching degree with the character template in the character recognition process, the closer to 1.0.
  • Steps S13 and S14 are repeated while changing the position of the character area.
  • the processes in steps S13 and S14 are repeated until the character recognition process is completed for all of the allowable character area positions.
  • a position where Nc characters are present from the left can be assumed to some extent. Therefore, the allowable range of the character area position may be appropriately determined according to the assumed position.
  • step S12 When the character recognition processing is completed for all the allowable positions of the character area for the area size #k set in step S12, the data processing described below is performed for the character area with the higher evaluation value (step S12). S15).
  • step S15 first, as shown in FIG. 7, for each region position (i, j), the character recognition result and evaluation value having the first rank are selected. Further, from the character recognition results of all the region positions having the first rank, m C character recognition results and evaluation values having higher evaluation values are extracted. Further, an average value ⁇ k of the evaluation values of the extracted upper m C character recognition results is calculated.
  • k is an index representing the region size
  • ⁇ k represents an average value of the evaluation values of the upper m C character recognition results calculated corresponding to the region size #k.
  • the evaluation value-luminance value conversion plot image shown in FIG. Is generated.
  • the evaluation value-luminance value conversion plot image refers to the character recognition result for each of the m C character recognition results having the highest evaluation value among the character recognition results of all region positions having the first rank.
  • the pixel corresponding to the region position (i, j) is an image generated as having a luminance value corresponding to the evaluation value of the character recognition result.
  • a non-zero luminance value is given for m C pixels.
  • the brightness value of other pixels is set to 0.
  • the predetermined value m C is a value that is appropriately determined to be larger than N C , and a value that is several times (for example, five times) N C is preset as the predetermined value m C.
  • FIG. 8 shows an example of an evaluation value-luminance value conversion plot image.
  • the evaluation value-luminance value conversion plot image corresponding to the region size #k is indicated by reference numeral 24-k.
  • n S is the number of possible region sizes.
  • the evaluation value-luminance value conversion plot image is used to determine the character position and the character size.
  • step S12 the character area size is set while changing the character area size used in the immediately preceding process from the character area size based on the x-direction increment and the y-direction increment. Further, since step S15 is performed for each region size, as a result, as shown in FIG. 9, an average evaluation value ⁇ k is obtained for each region size #k.
  • step S16 After all the possible character area sizes are processed in steps S12 to S15, a character area size determination process is performed (step S16). In step S16, the highest corresponding area size to those of the average value mu k calculated in step S15 is finally employed as the character area size. As will be described later, the character area size employed in step S16 is used for character recognition processing for the N C +1 and subsequent characters.
  • the character position and character size of each character are determined (step S17).
  • the character position of each character is defined as the center of the character area corresponding to the character, and the inter-character size is defined as an interval between character positions of adjacent characters.
  • FIG. 10 is a conceptual diagram showing the procedure for determining the character position and the inter-character size in step S17.
  • an evaluation value-luminance value conversion plot image corresponding to the character region size employed in step S16 is selected (step S21). If the character area size adopted in step S16 is the area size #k, the evaluation value-luminance value conversion plot image 24-k is selected.
  • the selected evaluation value-luminance value conversion plot image is subjected to a binarization process for binarization with a predetermined luminance threshold, and an image obtained by the binarization process (binarized image) Is subjected to a labeling process (step S22).
  • the labeling process is a process for assigning the same label to consecutive pixels of the same color (white or black) for the binarized image.
  • binarization processing is performed assuming that pixels whose luminance value is higher than the luminance threshold value are “white” pixels, and other pixels are “black” pixels.
  • the same label is given to a set of consecutive “white” pixels.
  • FIG. 10 shows an example in which four labels # 1 to # 4 are given in step S22.
  • step S23 If the number of labels determined in step S22 is greater than the number of characters to be subjected to character recognition processing in step S01 (that is, the designated number of characters N C ), labels that are inappropriate as character positions are eliminated (Ste S23).
  • step S23 firstly, for each label #L, average mu L of the evaluation value is calculated.
  • the luminance value of each pixel belonging to each label corresponds to the evaluation value of the character recognition result of the character area at the position of the pixel, and the average value of the evaluation values corresponding to the pixels belonging to the label #L is ⁇ L Calculated.
  • the barycentric position of each label #L is calculated. Since each label #L is composed of one or a plurality of pixels, the barycentric position of each label #L is calculated from the positions of the pixels belonging to the label #L.
  • each label is associated with each of the N C characters from the left end.
  • the pixel having the highest evaluation value of the corresponding character recognition result is selected, and the position of the pixel of the character recognition result having the highest evaluation value is determined as the character position of each character (step) S24).
  • the character position of each character is defined as the center position of the corresponding character area.
  • the inter-character size (that is, the character spacing) is determined based on the calculated distance.
  • the inter-character size is determined by calculating the plurality of distances. For example, the calculated average value of the plurality of distances may be used as the inter-character size.
  • the inter-character size determined in step S24 is used for the character recognition processing for the N C +1 and subsequent characters.
  • the character recognition result for the character region located at the character position of each character determined in step S17 and having the character region size determined in step S16 is selected as the character recognition result for each character ( Step S18).
  • the optimal character area size i.e., character region size determined in step S16
  • the optimum character size i.e., step S17
  • the inter-character size determined in (1) is obtained.
  • Step S02 Subsequently, character recognition processing is performed on the remaining characters (in this embodiment, the characters after the N C +1 character from the left).
  • the optimum character area size and inter-character size obtained in the above-described processing are used, thereby reducing the search range in the character recognition processing.
  • FIG. 11 is a diagram for explaining the character recognition process of the N C +1 character.
  • the character position (determined in step S17 described above) shifted from the character position of the N C character in the x-axis direction by the optimum inter-character size D X obtained in the above process.
  • the reference position of the character position of the N C +1 character is determined.
  • the character area is set while sequentially changing the position between the reference position and the surrounding area, and character recognition processing is performed for each set character area.
  • the reference size (width and height) of the character area to be set the optimum character area size obtained by the above processing is used.
  • the reference size width and height
  • the size in the x direction (ie, width) is indicated by the symbol “W”, and the size in the y direction (ie, height) is indicated by the symbol “H”. ing.
  • the width and height of the character area set in the character recognition process are set while sequentially changing the width and height of the reference size and the surrounding area. Further, the character recognition result (that is, the recognized character) having the highest evaluation value calculated in the character recognition process and the position of the character area are determined as the character recognition result and the character position of the N C +1 character.
  • the reference position of the character position of the N C +2 character is determined at a position shifted in the x-axis direction by the inter-character size D X from the character position of the N C +1 character (determined by the above-described processing).
  • the character area is sequentially changed by changing the position of the character area between the reference position and the surrounding area, and the width and height of the character area are changed to the width and height of the reference size and the surrounding area.
  • the character recognition process is performed for each set character area.
  • the character recognition result that is, the recognized character
  • the character area position having the highest evaluation value calculated in the character recognition process are determined as the character recognition result and the character position of the N C + 2nd character. Thereafter, the same processing is repeated until the character recognition processing is completed for all characters.
  • the type of the license plate is specified by the information on the inter-character size obtained by the above processing, and N C
  • processing corresponding to the specified type of license plate may be performed. For example, a countermeasure process for a specific similar character may be performed.
  • the character recognition process is performed without performing the binarization process on the plate area image. For this reason, the problem accompanying a binarization process can be avoided. For example, character recognition is possible even if the plate area image has a non-uniform luminance portion.
  • the character recognition process for the remaining characters is performed using the information on the character area size and the inter-character size obtained in the character recognition process for the NC character from the end. The search range in the character recognition process for the remaining characters can be reduced.
  • the character recognition process for the remaining characters is performed using both the character area size and the inter-character size information obtained in the character recognition process for the NC character from the end.
  • the character recognition processing for the remaining characters may be performed using only one of the size and the size between characters. Even in this case, the effect of reducing the search range can be obtained.
  • the character recognition processing is performed in order from the left character, but the order may be reversed.
  • character recognition processing may be performed in order from the right character.
  • the character recognition process may be performed in order from the upper character, and conversely, the character recognition process may be performed in order from the lower character.
  • the character recognition processing described above may be performed twice in the order opposite to each other, and the character recognition results obtained by the character recognition processing may be compared. In this case, when a character recognition result of a certain character is different, a character recognition result having a high evaluation value may be selected as a final character recognition result of the character.
  • the character recognition process and the evaluation value of each character are obtained by performing the character recognition processing in order from the left character. Furthermore, the character recognition process and the evaluation value of each character are obtained by performing the character recognition processing in order from the right character. More specifically, first, the right N C characters by performing the same process as in step S01, after obtaining the character recognition result and the evaluation value of the N C characters, similarly to step S02 for the remaining characters The character recognition result and evaluation value of the remaining characters are obtained. In this case, for the remaining characters, a character recognition result and an evaluation value are obtained in order from the right character.
  • the character recognition result obtained by performing the character recognition processing in order from the left character is compared with the character recognition result obtained by performing the character recognition processing in order from the right character.
  • the same character recognition result is selected as the final character recognition result of the character.
  • a character recognition result having a high evaluation value is selected as the final character recognition result of the character.
  • the character area size and the character interval size are determined based on the result of the area without the shadow (resulting in the high evaluation value). Therefore, the recognition accuracy can be improved.
  • the character recognition result when a character (similar character) that is likely to be erroneously recognized is known, when the similar character is obtained as the character recognition result, the character recognition result and the evaluation value
  • the character area size may be determined without using. Examples of similar characters include B and 8, D and 0, 7 and Z, and the like.
  • step S15 the character recognition result and the evaluation value that are ranked first for each region position (i, j) are selected, and further, from among the character recognition results of all the region positions that are ranked first.
  • the evaluation value is carried out a process of extracting m C-number of the character recognition result of the upper and evaluation value, the character recognition result and the evaluation values of m C-number except for character recognition result is similar characters may be extracted .
  • the average value ⁇ k is calculated as the average value of the evaluation values of the upper m C character recognition results, excluding the character recognition results of similar characters.
  • the list of similar characters may be stored in an appropriate storage unit (for example, the external storage device 4).
  • the present invention has been specifically described above, but the present invention is not limited to the above embodiment. It will be apparent to those skilled in the art that the present invention can be implemented with various modifications. For example, in the above description, an embodiment in which the present invention is applied to license plate recognition (recognition of characters written on a license plate) is described. However, the present invention generally recognizes characters for a captured image that is a grayscale image. Applicable.

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  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Character Discrimination (AREA)
  • Character Input (AREA)
  • Traffic Control Systems (AREA)

Abstract

La présente invention concerne un dispositif de reconnaissance de caractères qui réalise la reconnaissance de caractères sur une image à niveaux de gris contenant une chaîne comprenant des caractères alignés dans une direction spécifique. Ledit dispositif de reconnaissance de caractères réalise tout d'abord la reconnaissance de caractères sur NC caractères (NC étant un nombre prescrit supérieur ou égal à 2) à partir de la fin de la chaîne. Pendant la reconnaissance de caractères réalisée sur lesdits NC caractères, une pluralité de régions de caractères de différentes tailles de région de caractères sont définies à chaque position de l'image à niveaux de gris, et un résultat de reconnaissance de caractères ainsi qu'une note sont calculés pour chacune desdites régions de caractères. En se basant sur les notes calculées, le dispositif de reconnaissance de caractères détermine le résultat de la reconnaissance de caractères pour les NC caractères et la taille de région de caractères optimale. Pour la reconnaissance de caractères des caractères restants, le dispositif de reconnaissance de caractères définit une région de caractères ayant la taille de région de caractères optimale à chaque position sur l'image à niveaux de gris et réalise le processus de reconnaissance de caractères.
PCT/JP2013/079119 2013-02-25 2013-10-28 Dispositif de reconnaissance de caractères, procédé de reconnaissance de caractères et support d'enregistrement WO2014129016A1 (fr)

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SG11201506566YA SG11201506566YA (en) 2013-02-25 2013-10-28 Character recognition apparatus, character recognition method, and recording medium

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JP2013035160A JP6173715B2 (ja) 2013-02-25 2013-02-25 文字認識装置、文字認識方法及びプログラム
JP2013-035160 2013-02-25

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JP2021093225A (ja) * 2021-03-19 2021-06-17 キヤノン株式会社 情報処理装置、プログラム、情報処理方法

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH06215293A (ja) * 1993-01-19 1994-08-05 Hitachi Ltd 車番認識装置
JPH09282417A (ja) * 1996-04-18 1997-10-31 Matsushita Electric Ind Co Ltd 文字認識装置
JP2007188512A (ja) * 2000-09-29 2007-07-26 Japan Science & Technology Agency 文字認識方法、文字認識プログラム及び文字認識プログラムを記録したコンピュータ読み取り可能な記録媒体
JP2011018175A (ja) * 2009-07-08 2011-01-27 Mitsubishi Heavy Ind Ltd 文字認識装置及び文字認識方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH06215293A (ja) * 1993-01-19 1994-08-05 Hitachi Ltd 車番認識装置
JPH09282417A (ja) * 1996-04-18 1997-10-31 Matsushita Electric Ind Co Ltd 文字認識装置
JP2007188512A (ja) * 2000-09-29 2007-07-26 Japan Science & Technology Agency 文字認識方法、文字認識プログラム及び文字認識プログラムを記録したコンピュータ読み取り可能な記録媒体
JP2011018175A (ja) * 2009-07-08 2011-01-27 Mitsubishi Heavy Ind Ltd 文字認識装置及び文字認識方法

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