JP4923223B2 - Magnetic character recognition method and magnetic character recognition device - Google Patents

Description

  The present invention relates to a magnetic character recognition method and a magnetic character recognition device that read a character string printed with magnetic ink characters, generate a reproduction waveform, and perform character recognition, and in particular, can perform character recognition with high accuracy. About things.

  Conventionally, various methods have been disclosed in which a character print portion on the surface of a medium on which magnetic ink characters (MICR characters) are printed is read by a magnetic head to obtain a magnetic reproduction signal, and character recognition is performed using the magnetic reproduction signal. . Magnetic ink characters (MICR characters) are used in checks and the like handled by financial institutions and the like. Typical character types are E13B and CMC7, and are standardized by ISO1004 and the like.

  At the early stage of MICR character recognition technology development, the mainstream method is to read a magnetic character line with a magnetic head, input the magnetic reproduction signal waveform to a logic circuit, and perform character recognition based on the characteristics of the peak position and its output level. However, in recent years, with the increase in performance of microprocessors and the increase in speed and capacity of storage elements, the number of characters that are recognized by processing magnetic signals with software has been increasing. In addition, there is an example in which not only a magnetic signal but also an image obtained by image scanning of a medium is used in combination.

  In the method using a magnetic signal, a method is disclosed in which the peak interval of a magnetic reproduction signal is determined and associated with a character represented by the combination pattern from the combination of the magnitudes (see, for example, Patent Document 1).

JP 2001-351062 A

  However, some checks and the like that are actually distributed in the market are within the tolerances, but the printing state of magnetic ink characters is not good. Therefore, the character recognition technique is required to recognize characters on the boundary line and not to perform wrong character recognition.

  More specifically, the actual magnetic ink characters vary depending on the quality of the magnetic ink, the magnetic characteristics of the printing device, reproducing magnetic head and magnetizing head, and there are changes in high magnetic force, low magnetic force, bold / thin characters, inclination, etc. Arise. Furthermore, depending on the use state and storage state of the check, changes such as perforation, blurring, and blurring may occur, and the magnetic reproduction waveform of the magnetic ink character will be variously deformed. In particular, in the case of being stored after being folded, there is a possibility that the character width and the character pitch change when scanning the fold portion, leading to a decrease in recognition accuracy.

  Therefore, in the method disclosed in Patent Document 1 described above, the peak interval of the magnetic waveform is determined, and the interval pattern is converted to 1 when it is wider than the predetermined interval, and is converted to 0 when it is smaller than the predetermined interval. There are procedures. The presence / absence of an abnormality is detected based on whether the array pattern of 1 and 0 matches the regular pattern.

  However, according to the method disclosed in Patent Document 1, when the interval between the magnetic patterns is in the middle and between the narrow and narrow intervals, a determination error is likely to occur and there is a high possibility of erroneous recognition.

  The present invention has been made in view of these points, and an object thereof is a magnetic character recognition method capable of accurately recognizing magnetic characters even when there is a deformation of a magnetic waveform pattern. And a magnetic character recognition device.

  In order to solve the above problems, the present invention provides the following.

(1) Based on a reference waveform serving as a reference when a character string composed of a plurality of magnetic characters printed using magnetic ink is read by a magnetic head, the peak constituting the reference character waveform for each character of the magnetic character Waveform generation for generating a reproduction waveform from an array data preparation step for preparing reference peak interval array data from an array pattern of intervals between a plurality of peaks included, and a character string of magnetic characters printed on the surface of an information recording medium A peak interval array data is generated from a step, a cutout step of cutting out a character waveform of each magnetic character from the reproduced waveform, and an array pattern of intervals between peaks included in the peaks constituting the character waveform wherein the arrangement data generating process of, and the array data of peak intervals, and a comparison step of comparing the reference array data of peak intervals, the cutout Engineering In this case, depending on whether or not there is a peak greater than or equal to a predetermined intensity value within the length of one character, it is determined whether the reproduced waveform of that portion corresponds to a character area or a non-signal area In the clipping step, the predetermined intensity value is obtained for all peak values included in the reproduced waveform, and the variance of peaks within a certain range is obtained from the average value of the reproduced waveform, and based on the variance value is determined, based on the comparison result of the comparing step, the magnetic character recognition method characterized by determining a character corresponding to the best match high degree of array data of peak intervals as read characters.

  According to the present invention, first, reference inter-peak interval arrangement data is prepared from an arrangement pattern of intervals between a plurality of peaks included in a peak constituting a reference character waveform for each magnetic character. Thereafter, a reproduction waveform is generated from the character string of the magnetic character, the character waveform for each character is cut out, and peak interval array data is generated from an array pattern of intervals between peaks included in the peaks constituting the character waveform. The peak interval array data is compared with the reference peak interval array data, and as a result, the character corresponding to the peak interval array data having the highest degree of coincidence is determined as the read character, so that magnetic character recognition is performed with high accuracy. Can do.

  In other words, the magnetic character recognition method according to the present invention does not require large / small comparison between peaks or pattern conversion processing, and therefore, the magnetic character recognition method is in the middle of the interval between when the magnetic pattern interval is wide and when it is narrow. However, it is difficult to make a judgment mistake. As a result, the accuracy of magnetic character recognition can be improved.

  (2) In the magnetic character recognition method, the correlation coefficient between the peak interval arrangement data and the reference peak interval arrangement data is compared, and the character corresponding to the correlation coefficient having the highest degree of coincidence is determined as a read character. (1) The magnetic character recognition method according to (1).

  According to the present invention, the magnetic character recognition method described above compares the correlation coefficient between the peak interval array data and the reference peak interval array data, and uses the character corresponding to the correlation coefficient with the highest degree of matching as a read character. Since the determination is made, it is not necessary to convert the peak-to-peak distance into a distance pattern or the like, which can contribute to a reduction in processing load.

In previous SL-cutting process step, 1 within the length of the character, depending on whether a predetermined intensity value or more peaks are present, the corresponding reproduction waveform of that portion, the non-signal area or to correspond to the character region it you wherein determining whether to.

  According to the present invention, in the above-described clipping step, the reproduced waveform of the portion is made to correspond to the character region depending on whether or not a peak having a predetermined intensity value or more exists within the length of one character. Therefore, it is difficult to be affected by noise, and as a result, the accuracy of magnetic character recognition can be improved.

Determined in the previous SL-cutting process step, the predetermined intensity value, all peak values included in the reproduced waveform determined, determine the variance of the peaks from the mean value of the reproduction waveform within a certain range, based on the variance value It is the fact that to said.

  According to the present invention, in the clipping step described above, the predetermined intensity value described above obtains all peak values included in the reproduced waveform, obtains the variance of peaks within a certain range from the average value of the reproduced waveform, Since it is determined based on the variance value, it is difficult to be affected by fluctuations in the noise level due to the individuality of the recognition processing system, and as a result, it can contribute to improving the accuracy of magnetic character recognition.

( 3 ) Based on a reference waveform used as a reference when reading a character string composed of a plurality of magnetic characters printed using magnetic ink with a magnetic head, the peak constituting the reference character waveform for each character of the magnetic character Waveform generation that generates a reproduction waveform from an array data storage unit that stores an array pattern of intervals between a plurality of peaks as reference peak interval array data and a character string of magnetic characters printed on the surface of an information recording medium Generating peak interval array data from a reproduction portion, a cutout portion for cutting out a character waveform of each magnetic character from the reproduction waveform, and an array pattern of intervals between peaks included in the peaks constituting the character waveform A sequence data generation unit, a comparison unit that compares the peak interval sequence data and the reference peak interval sequence data, and in the cutout unit Depending on whether or not there is a peak greater than or equal to a predetermined intensity value within the length of one character, it is determined whether the reproduced waveform of that part corresponds to a character area or a non-signal area. In the cut-out unit, the predetermined intensity value is determined based on a dispersion value obtained by obtaining all peak values included in the reproduced waveform, obtaining a dispersion of peaks within a certain range from the average value of the reproduced waveform. And determining a character corresponding to the peak interval array data having the highest degree of coincidence as a read character based on the comparison result of the comparison unit.
(4) The comparison unit compares a correlation coefficient between the peak interval array data and the reference peak interval array data, and determines a character corresponding to the correlation coefficient with the highest degree of matching as a read character. The magnetic character recognition device according to (3), characterized in that it is characterized in that:

  According to the present invention, the magnetic character recognition device is provided with the sequence data storage unit, the waveform generation unit, the cutout unit, the sequence data generation unit, and the comparison unit. Based on the comparison result of the comparison unit, Since the character corresponding to the peak interval arrangement data when the degree of coincidence between the peak interval arrangement data and the reference peak interval arrangement data is the highest is determined as a read character, magnetic character recognition can be performed with high accuracy.

  According to the present invention, the character corresponding to the peak interval array data having the highest degree of coincidence is determined as the read character by comparing the peak interval array data with the reference peak interval array data. Even if there is a deformation, magnetic character recognition can be performed with high accuracy.

  The best mode for carrying out the present invention will be described below with reference to the drawings.

[Magnetic character recognition device]
FIG. 1 is a schematic diagram showing a configuration of a magnetic character recognition device 1 according to an embodiment of the present invention. In the embodiment of the present invention, a check reader having a MICR recognition function will be described as an example. In FIG. 1, the structure centering on the part regarding the MICR character recognition process of the magnetic character recognition apparatus 1 which concerns on embodiment of this invention is shown.

  In FIG. 1, a magnetic character recognition device 1 detects a paper medium conveyance path 11, a magnetizing head 12 that remagnetizes MICR characters (magnetic ink characters printed using magnetic ink), and magnetism of the MICR characters. A magnetic head 13, a roller 14 for conveying a paper medium, a magnetic head driving / amplifying circuit 15, a medium conveyance control circuit 16, a microprocessor 17, and a RAM 18 are provided. The magnetic head 13 is controlled by a magnetic head drive / amplifier circuit 15, and the roller 14 is controlled by a medium transport control circuit 16. The magnetic head drive / amplifier circuit 15 and the medium transport control circuit 16 operate based on a command from a microprocessor 17 such as a CPU. The microprocessor 17 uses the RAM 18 as a working memory.

  The check (information recording medium) inserted into the paper medium conveyance path 11 is conveyed by the roller 14 and passes through the magnetizing head 12 and the magnetic head 13. The magnetized head 12 remagnetizes the MICR character printed on the check, and the magnetic head 13 detects the magnetism of the MICR character remagnetized by the magnetized head 12.

  A reproduction waveform is generated from the MICR characters read by the magnetic head 13 (waveform generation step by the waveform generation unit), and the generated reproduction waveform is digitized and recorded in a MICR waveform memory (for example, RAM 18). Using the MICR reproduction waveform data stored in the MICR waveform memory, a magnetic character recognition process is performed in the microprocessor 17 built in the magnetic character recognition apparatus 1. Details of the magnetic character recognition will be described in [Magnetic Character Recognition Method] described later.

  In the present embodiment, magnetic character recognition is performed by the microprocessor 17 built in the magnetic character recognition device 1. However, the MICR reproduction waveform is transferred to a higher-level control device (for example, ATM) and the higher-level control device. It is good also as performing magnetic character recognition. Further, a close contact type one-dimensional image sensor for reading an image on the surface of a check may be arranged on the upper part, the lower part or both sides of the paper medium conveyance path 11. Furthermore, it is good also as arrange | positioning the printing block for printing a predetermined matter on the check surface.

  FIG. 2 is a block diagram showing an electrical configuration of the magnetic character recognition apparatus 1 according to the embodiment of the present invention. FIG. 2 shows a configuration centering on a portion related to MICR character recognition processing.

  2, the magnetic character recognition device 1 includes a recognition control unit 100, a MICR waveform memory (for example, EEPROM) 101, a reference waveform database (for example, EEPROM) 102, a preprocessing unit 103, a peak detection unit 104, and the like. A character boundary detecting unit 105 and a character recognizing unit 107.

  The MICR reproduction waveform stored in the MICR waveform memory 101 is first subjected to noise removal of the entire MICR reproduction waveform by smoothing in the preprocessing unit 103 to generate a shaped waveform from which noise has been removed.

  Next, in the peak detection unit 104, all peak information included in the shaped MICR reproduction waveform is detected, and peak information such as polarity (positive / negative), intensity, and peak position of each peak is stored. . At this time, a peak exclusion process in which the peak intensity is less than a certain value is also performed.

  Next, based on these peak information, the character boundary detection unit 105 detects the first peak for each magnetic ink character from the MICR reproduction waveform, and cuts out a character waveform corresponding to one character (cutout unit). Cutting out step). Then, peak interval arrangement data is generated from an arrangement pattern of intervals between a plurality of peaks included in the peaks constituting the extracted character waveform (an arrangement data generation step by an arrangement data generation unit). Then, the character recognition unit 107 compares the peak interval arrangement data with the reference peak interval arrangement data stored in the reference waveform database 102 (comparison step by the comparison unit) to perform magnetic character recognition.

  Here, the reference waveform database 102 described above is a storage means including, for example, an EEPROM or a flash memory, and functions as an array data storage unit that stores reference peak interval array data used in the array data preparation process. Specifically, the reference waveform database 102 stores each character of a magnetic character based on a reference waveform that serves as a reference when a character string composed of a plurality of magnetic characters printed using magnetic ink is read by a magnetic head. An arrangement pattern of intervals between a plurality of peaks included in a peak constituting the reference character waveform is stored as reference peak interval arrangement data.

  In addition to the reference waveform database 102, the magnetic character recognition apparatus 1 according to the present embodiment may include a database that stores reference peak interval arrangement data corresponding to various deformation factors. That is, in the initial stage, when a character cannot be uniquely determined, it may be compared with the second and third databases.

[Magnetic character recognition method]
FIG. 3 is a flowchart showing an overall flow of the magnetic character recognition method according to the embodiment of the present invention.

  As shown in FIG. 3, in the magnetic character recognition method according to the present embodiment, first, smoothing is performed (step S1). Specifically, the entire MICR waveform is smoothed using a moving average method or the like, and high-frequency noise is removed to perform processing so that waveforms can be compared without being affected by noise.

  Next, peak detection is performed (step S2). Specifically, all the peaks included in the MICR reproduction waveform, that is, the maximum value and the minimum value are detected.

  A positive peak is detected as an upwardly convex pattern. That is, the difference between the signal output Amp (t) at the current time t and the previous signal output Amp (t + 1) is Δ (t) = Amp (t + 1) −Amp (t), where Δ (t)> 0 and Δ ( When t + 1) <0, it is determined that Amp (t + 1) is a positive maximum value. A negative peak is detected as a downwardly convex pattern. That is, when Δ (t) <0 and Δ (t + 1)> 0, Amp (t + 1) is determined to be a negative maximum value (minimum value).

  The positive and negative peaks appear alternately. Each time a peak is detected, its index t, signal output Amp (t), and polarity Sgn are stored. In addition, when the same signal output value forms one peak continuously, the peak shape is trapezoidal. Therefore, the start position and end position of the flat part of the peak are obtained, and the intermediate point between the two is obtained. Are determined to be peak positions. By doing so, the peak position can be accurately detected even when the MICR magnetic reproduction output of the check is saturated.

  Next, peak threshold value determination processing is performed (step S3). The peak threshold is used to determine whether a peak included in the reproduced waveform is noise or a true peak. Even if it is determined that a certain signal output value is a peak, if the signal output level is less than a certain value, it is determined that the signal is noise and not adopted. Thus, it is possible to perform accurate magnetic character recognition without being affected by noise.

  FIG. 4 is a flowchart for explaining in detail the peak threshold value determining process in step S3 in FIG. In FIG. 4, first, an average value Pav of the entire reproduced waveform is obtained (step S11). Of the peaks obtained by the peak detection process (step S2 in FIG. 3), those satisfying Pav−R ≦ Pk ≦ Pav + R with respect to R (> 0) having an appropriate level value Pk are extracted (step S12). . Then, the average value Pm and standard deviation Ps of the extracted peaks are calculated (step S13). An appropriate value may be used for R in consideration of the characteristics of the magnetic reproducing circuit system.

  Finally, the peak threshold value Ath is calculated using a calculation formula of Ath = Pm + δPs (step S14). Note that 3 or 4 is used for δ. Thus, an appropriate peak value can be set without being affected by variations in signal level.

  As described above, in the flowchart shown in FIG. 4, in determining the peak threshold value Ath, all peak values included in the reproduced waveform are obtained, and the dispersion (or standard deviation) of peaks within a certain range from the average value of the reproduced waveform. ) And is determined based on the dispersion value (or standard deviation).

  In the present embodiment, the standard deviation is used to determine the peak threshold value Ath, but other values may be used. That is, it is determined whether the reproduction waveform of the portion corresponds to the character region or the non-signal region depending on whether or not a peak having a predetermined intensity value or more exists in the length range of one character. It is good as well. In FIG. 3, for the sake of convenience of explanation, the peak threshold value determination process in step S3 and the character cutout process in step S4 are described separately. However, the peak threshold value determination process in step S3 is the same as the character cutout process in step S4. It may be included.

  Next, character segmentation is performed (step S4). FIG. 5 is a flowchart showing a detailed flow of “character segmentation” (step S4) in the flowchart shown in FIG. 3, and FIG. 6 is a diagram showing an example of MICR reproduction waveform data.

  In character segmentation, first, the beginning peak position of a character is detected. The leading peak of the character is defined as a major peak having a signal output value of a certain level or higher according to the standard related to MICR character printing. It is determined whether or not the value Pk is positive and equal to or greater than the peak threshold value Ath. For this threshold value, for example, an average value is obtained for all positive peak values, and is set to a value of 60% thereof.

  In FIG. 5, 1 is substituted into variable i and variable k, and position information IDX (i) (that is, IDX (1)) is substituted into NEXTPEAK (step S21). When the level value Pk (i) is positive (positive / negative is detected using the polarity function Sgn (i)) and is equal to or higher than the peak threshold value Ath, whether IDX (i) is larger than NEXTPEAK-USIZE. Is determined (step S22). If this is not larger than NEXTPEAK-USIZE, it is determined that IDX (i) at that time is not a character cut-out part, and after incrementing i (step S24), the process proceeds to step S22 until i becomes last. return.

  On the other hand, when IDX (i) is larger than NEXTPEAK-USIZE (that is, when the value is higher than NEXTPEAK-USIZE and exceeds the peak threshold Ath and a positive level value Pk (i)), IDX (i) at the time is determined to be a character cut-out portion, and the IDX (i) is substituted into BGN (k) (step S23). Further, IDX (i) + PITCH (character spacing) is substituted for NEXTPEAK, and the variable k is incremented by one. As a result, the position information IDX (1) of Pk (1) shown in FIG. 6 is assigned to BGN (1), and the position information IDX (17) of Pk (17) shown in FIG. 6 is assigned to BGN (2). Will be. The same applies to BGN (3) and thereafter.

  In this way, the detection of the leading peak of the character is continued, and when the end of the MICR character waveform is exceeded (step S25: YES), the character segmentation is terminated. Note that the above-mentioned USIZE represents the number of points before the top peak of the character waveform. That is, the reference waveform data is created so that the first peak comes from the top of the reference waveform. Accordingly, a point having the same length as that of the reference waveform is cut out with a point before USIZE from the top peak as a cut start point.

  Here, in step 22 of FIG. 5, while NEXTPEAK (-USIZE) is not reached, the peaks in between are sequentially detected, and the distances between adjacent peaks are successively stored. In this case, the calculation of the distance between adjacent peaks is performed for either the positive peak or the negative peak.

  Thus, the detection of the leading peak of the character and the calculation of the distance between adjacent peaks are continued, and the character cut-off is terminated when the end of the MICR character waveform is exceeded. In the case of CMC7 font, one character is composed of 7 bars and 6 spaces. The distance between peaks is composed of 6 pieces of data per character.

  When the peak-to-peak distance for the i-th character is expressed as Di1, Di2, Di3, Di4, Di5, Di6, in the example of FIG. 6, D11 = Pk (3) −Pk (1), D12 = Pk (5) − Pk (3),..., D16 = Pk (13) −Pk (11).

  Next, character recognition is performed (step S5 in FIG. 3).

  FIG. 7 is a flowchart showing a detailed flow of “character recognition” (step S5) in the flowchart shown in FIG. FIG. 8 is a diagram showing an example of magnetic character lines printed on a medium such as a check. Reading of the magnetic pattern is performed from right to left in FIG. By processing the read magnetic reproduction waveform in the above-described character extraction step, a data array of adjacent peak-to-peak distances shown in [Table 1] is obtained (step S31).

次に、文字ごとにピーク間距離のデータ配列を、予め用意された［表２］（下記参照）のテンプレートのデータ配列（標準パターン配列）のそれぞれと逐次比較する（ステップＳ３２）。なお、本実施形態では、一致度（一致係数）の尺度としては、正規化相関を用いている。

Next, the data arrangement of the distance between peaks for each character is sequentially compared with each of the template data arrangement (standard pattern arrangement) of [Table 2] (see below) prepared in advance (step S32). In the present embodiment, normalized correlation is used as a measure of the degree of coincidence (coincidence coefficient).

例えば、図８の一番先頭（右端）の文字について、この文字のピーク間距離は、Ｄ１＝（Ｄ１６，Ｄ１５，Ｄ１４，Ｄ１３，Ｄ１２，Ｄ１１）である。そして、このＤ１と、標準パターンの１番目、すなわち数字の"１"を示すＴ１＝（１，０，０，０，１，０）との相関係数Ｒ（１，１）を求める。

For example, for the first character (right end) in FIG. 8, the distance between the peaks of this character is D1 = (D16, D15, D14, D13, D12, D11). Then, a correlation coefficient R (1, 1) between D1 and T1 = (1, 0, 0, 0, 1, 0) indicating the first standard pattern, that is, the numeral “1” is obtained.

次に、数字の"２"を示すＴ２との相関係数Ｒ（１，２）を求める。以下同様に、記号"ＳＶ"までの各テンプレートデータとの相関係数Ｒ（１，ｔ）を求める。最後に、これら相関係数の最大値Ｒｍ＝ｍａｘ（Ｒ（１，ｔ）を求め、そのときのｔに対応する文字が求める認識結果となる。

Next, a correlation coefficient R (1,2) with T2 indicating the number “2” is obtained. Similarly, a correlation coefficient R (1, t) with each template data up to the symbol “SV” is obtained. Finally, a maximum value Rm = max (R (1, t) of these correlation coefficients is obtained, and a character corresponding to t at that time is obtained as a recognition result.

  Then, whether or not the matching degree is sufficient is determined based on whether Rm is larger or smaller than a predetermined value (step S33). If Rm is smaller than a predetermined value, it is determined that the waveform is abnormal and the character cannot be specified (step S35). If Rm is larger than the predetermined value, character determination is performed (step S34). . Note that, other than setting “character cannot be specified” in step S35, for example, the waveform analysis may be further limited to only those having similar degrees of similarity.

  Thus, in step S33, that is, when the correlation coefficient between the peak interval array data and the reference peak interval array data is compared, and the correlation coefficient having the highest degree of matching is greater than a predetermined value, The character corresponding to the correlation coefficient is determined as the read character.

  Next, it is determined whether or not it is the last character (step S36). If it is not the last character, the process proceeds to step S31. On the other hand, if it is the last character, this subroutine is terminated. As a measure of similarity, in addition to the normalized correlation used in the present embodiment, the sum of absolute differences can be used as appropriate. Moreover, although there are standards such as E13-B and CNC-7 for MICR characters, the present invention can be applied to any MICR character.

[Effect of the embodiment]
As described above, according to the magnetic character recognition device 1 and the magnetic character recognition method according to the present embodiment, the distance between adjacent peaks in the magnetic reproduction waveform for one character is obtained, and the array (peak) of the distance data is obtained. (Interval array data) is generated and the pattern is compared with the character pattern bit array dictionary (reference peak interval array data) obtained in advance. -There is no need for small comparisons and pattern conversion processing, which can contribute to improving the accuracy of magnetic character recognition.

  More specifically, unlike the known example, it is not necessary to examine the magnitude relationship between the distances between individual peaks and convert them into distance patterns, and the correlation coefficient is simply obtained, so that the processing is simplified. Also, in the case where the distance between peaks is between the large and small, the second conversion process is provided in the known example, but in this embodiment, even if there is a fluctuation in the distance between peaks, the similarity as the whole character is similar. Since the character is determined by quantifying, the character recognition can be performed with high accuracy.

  Further, even when the character set to be used is changed, it is only necessary to prepare standard data corresponding to the character set, so that the maintainability of the magnetic character recognition device 1 can be improved.

  Further, in the above-described peak threshold determination (step S3 in FIG. 3) or character segmentation (step S4 in FIG. 3), whether or not a peak having a predetermined intensity value or more exists within the length of one character. Therefore, since it is determined whether the reproduced waveform of the portion corresponds to the character area or the non-signal area, it is hardly affected by noise. Since the predetermined intensity value is determined based on the variance value of the peaks within a certain range from the average value of the reproduced waveform, it is affected by fluctuations in the noise level due to the individuality of the recognition processing system. Hateful.

  In the embodiment described above, the printed characters on the medium are numbers and symbols, but depending on the medium, alphabets may also be used. In that case, since the existence ratio of the large peak interval and the small peak interval in the character changes, in the known example, it is necessary to add processing logic corresponding thereto. However, in the present embodiment, it is only necessary to add an alphabetic part to the reference data table of Table 2 described above, so that it is possible to flexibly cope with variations of recognition targets.

  The magnetic character recognition method and the magnetic character recognition device according to the present invention are useful as those capable of improving the accuracy of magnetic character recognition.

It is a schematic diagram which shows the structure of the magnetic character recognition apparatus which concerns on embodiment of this invention. It is a block diagram which shows the electrical constitution of the magnetic character recognition apparatus which concerns on embodiment of this invention. It is a flowchart which shows the whole flow of the magnetic character recognition method which concerns on embodiment of this invention. It is a flowchart for demonstrating in detail the peak threshold value determination process of step S3 in FIG. In the flowchart shown in FIG. 3, it is a flowchart which shows the detailed flow of "character cutting out" (step S4). It is a figure which shows an example of MICR reproduction waveform data. In the flowchart shown in FIG. 3, it is a flowchart which shows the detailed flow of "character recognition" (step S5). It is a figure which shows an example of the magnetic character line printed on media, such as a check.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Magnetic character recognition apparatus 11 Paper medium conveyance path 12 Magnetization head 13 Magnetic head 14 Roller

Claims (4)

A plurality of peaks included in a reference character waveform for each character of a magnetic character based on a reference waveform serving as a reference for reading a character string composed of a plurality of magnetic characters printed using magnetic ink with a magnetic head. An array data preparation step of preparing reference peak interval array data from an array pattern of intervals between peaks of
A waveform generating step for generating a reproduction waveform from a character string of magnetic characters printed on the surface of the information recording medium;
From the reproduced waveform, a cutting process to cut out the character waveform for each character of the magnetic character,
An array data generation step for generating peak interval array data from an array pattern of intervals between a plurality of peaks included in the peaks constituting the character waveform;
Comparing the peak interval sequence data with the reference peak interval sequence data,
In the clipping step, depending on whether or not there is a peak greater than or equal to a predetermined intensity value within the length of one character, the reproduced waveform at that portion is made to correspond to the character region or to the non-signal region. Determine whether
In the clipping step, the predetermined intensity value is determined based on a dispersion value obtained by obtaining all peak values included in the reproduced waveform, obtaining a variance of peaks within a certain range from the average value of the reproduced waveform. ,
A magnetic character recognition method, wherein a character corresponding to peak interval array data having the highest degree of coincidence is determined as a read character based on a comparison result of the comparison step.   In the magnetic character recognition method, the correlation coefficient between the peak interval arrangement data and the reference peak interval arrangement data is compared, and the character corresponding to the correlation coefficient having the highest degree of coincidence is determined as a read character. The magnetic character recognition method according to claim 1. A plurality of peaks included in a reference character waveform for each character of a magnetic character based on a reference waveform serving as a reference for reading a character string composed of a plurality of magnetic characters printed using magnetic ink with a magnetic head. An array data storage unit for storing an array pattern of intervals between peaks as reference peak interval array data;
A waveform generator for generating a reproduced waveform from a character string of magnetic characters printed on the surface of the information recording medium;
A cutout unit that cuts out a character waveform for each character of the magnetic character from the reproduced waveform;
An array data generation unit for generating peak interval array data from an array pattern of intervals between a plurality of peaks included in the peaks constituting the character waveform;
A comparison unit for comparing the peak interval arrangement data and the reference peak interval arrangement data,
In the cutout unit, depending on whether or not there is a peak of a predetermined intensity value or more within the range of the length of one character, the reproduced waveform of that portion is made to correspond to the character region or to the non-signal region. Determine whether
In the clipping unit, the predetermined intensity value is determined based on a dispersion value obtained by obtaining all peak values included in the reproduced waveform, obtaining a variance of peaks within a certain range from the average value of the reproduced waveform. ,
A magnetic character recognition apparatus, wherein a character corresponding to peak interval array data having the highest degree of coincidence is determined as a read character based on a comparison result of the comparison unit. The comparison unit compares a correlation coefficient between the peak interval arrangement data and the reference peak interval arrangement data, and determines a character corresponding to the correlation coefficient with the highest degree of matching as a read character. The magnetic character recognition device according to claim 3.

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