OPTICAL CHARACTER RECOGNITION APPARATUS

Abstract: The invention relates to a character recognition apparatus which comprises a scanner (1) for optically scanning a prescribed scanning area and outputting a scanned signal corresponding to a character contained in the scanning area, a binary processing circuit (2) receiving the scanned signal from the scanner(1) for producing a plurality of binary signals different in a characteristic by means of alteration of a threshold level and/or a filtering process, a black mesh number counting means (7) for counting black meshes in the scanning area with respect to the plurality of the binary signals when the scanning area is represented by a large number of meshes and when the binary signals are represented in each mesh by black showing a part of a character and by white showing a background other than the character or the mark, an insulated mesh counting means (9) for counting insulated meshes each being a white mesh surrounded by black meshes and a black mesh surrounded by white meshes with respect to the plurality of the binary signals, a ratio calculating means (10) for calculating ratios of the number of black meshes with that of the insulated meshes with respect to the plurality of the binary signals and a selecting means (11) for selecting one optimum binary signal from the plurality of the binary signals on the basis of comparison of the ratios. Accordingly, a recognition processing is performed on the basis of the selected optimum binary signal.

Description: Background of the Invention The present invention relates to an optical character recognition apparatus which optically scans characters such as a letter and a mark written on a mail article and performs character recognition based on a scanned signal. In an optical character recognition apparatus, a character is recognized in such a manner that the character is scanned optically and a binary signal is produced from the scanned signal by slicing the scanned signal by a threshold level. Then, distinctive features of the character are extracted from the binary signal and are compared with reference features. In the binary signal processing, optimization of setting of the threshold level is conducted to improve a recognition rate. Further, to this end, filtering processes such as thinning, gradating and emphasizing processes are also conducted to produce a effective binary signal. In the case of a mail article as an object to be read, however, a character is frequently written or printed in various conditions, for example, in a variety of brightness and color of a background and in a variety of printed condition of strong to weak. In the case of the mail article, in addition, when a paper constructing the mail article is thin, another character and mark printed in an interior are sometimes picked up by a scanner through such thin paper. Therefore, it is difficult in this case to set an optimum threshold level and to perform an optimum filtering process irrespective of a various object to be read, and thus, the recognition rate can not be sufficiently improved. Namely, when the threshold level and the filtering process are set so as to sufficiently read a weakly printed/written character, for instance, the recognition rate becomes lower since a pattern other than the character is picked up and it becomes a noise in the binary signal. To the contrary, when the threshold level and the filtering process are set so as not to extract the pattern other than the character, a weakly printed written character can not be recognized. As above stated, it is difficult heretofore to increase the recognition rate sufficiently when the mail article having various printing conditions is scanned. US-A-3,668,637 determines an optimum binary signal by calculating the average width, which is a ratio between an area occupied by a black portion of the entire character stroke and the length of the entire character stroke along its center part. It is, therefore, an object to provide an optical character recognition apparatus which can recognize a character correctly even when the conditions of the character and the background are various. This object is solved with the features of the claims. Brief Description of Drawings Fig. 1 is a block diagram of a first embodiment according to the present invention; Fig. 2 is a block diagram of an isolated pixel or mesh extracting circuit in Fig. 1; Fig. 3 is a block diagram of a second embodiment according to the present invention; Fig. 4 is a block diagram of a third embodiment according to the present invention; Fig. 5 is a block diagram of a fourth embodiment according to the present invention; and Fig. 6 shows a example of quantized pixels or meshes corresponding to a binary signal. Description of preferred Embodiments In Fig. 1 showing a first embodiment of the present invention, a scanner 1 scans a scanning area having a predetermined dimension of a mail article, and a scanned signal is supplied to a binary processing circuit 2. In the binary processing circuit 2, the scanned signal supplied from the scanner 1 is sliced by different threshold levels or subjected to different filtering processes to form a plurality of binary signals B₁, B₂ and B₃ having respective different characteristics. Then, the binary signals B₁, B₂ and B₃ are supplied to signal quality determination circuits 3, 4 and 5, respectively. These binary signals B₁ to B₃ are quantized. It is assumed that the scanning area scanned by the scanner 1 is represented by 100 x 200 pixels or meshes, for instance, each pixel or mesh being black showing a part of a character or white showing a background. On the other hand, these binary signals B₁, B₂ and B₃ are supplied to a memory 6 and stored therein. The signal quality determination circuits 3, 4 and 5 have the same construction and each of them comprises a black mesh number counting circuit 7, an isolated (noise) mesh extraction circuit 8, a noise mesh counting circuit 9 and a ratio calculation circuit 10. The black mesh number counting circuit 7 receiving the binary signal B counts black meshes in the scanning area, and delivers the black mesh number e to the ratio calculation circuit 10. The noise mesh extraction circuit 8 receives the binary signal B and extracts an isolated (noise) mesh showing a central mesh alone different from surrounding ones in a region of some dimensions, e.g. a region of 3 x 3 meshes or 5 x 5 meshes. For instance, a case wherein meshes surrounding a central white mesh are all black, as well as a case wherein meshes sorrounding a central black mesh are all white, are to be extracted. In the present application, such isolated mesh as stated above is dealt with as noise. The construction of the isolated mesh extraction circuit 8 will be described later in detail. The output of the isolated mesh extraction circuit 8 is sent to the noise mesh counting circuit 9, wherein the number of isolated meshes in the scanning area is counted and the noise mesh number (f) is sent to the ratio calculation circuit 10. The ratio calculation circuit 10 receives the number (e) from the black mesh number counting circuit 7 and the number (f) from the noise mesh counting circuit 9 and calculates an evaluation ratio (f/e). In an optical character recognition apparatus, in general, the accuracy and stability of a recognition process increase as the aforementioned isolated (noise) meshes decrease and, accordingly, the evaluation ratio (f/e) can be applied to determine one binary signal being more appropriate for the recognition process. Now, it is assumed that two mail articles P and Q will be taken as examples. In the mail article P, depth gradation of print of character is small, while, in the mail article Q constructed of a thin paper, another character or mark printed at the back face is seen through. A description will be made on the adaptation of the present invention to these cases, citing the formation of two binary signals produced by two different threshold levels, i.e., high and low threshold levels. In the case of the mail article P, the signal quality of the binary signal is improved as the threshold level is lowered. To the contrary, if the threshold level becomes high, a binary signal produced thereby becomes to have blur. For instance, the number e₁ of black meshes is 1200 and the number f₁ of isolated (noise) meshes is 100 in the case where the scanning area of a scanner is of 100 x 200 meshes and when the threshold level is low. When the threshold level is raised in this case, the number e₂ of black meshes turns to be 800 while the number f₂ of noise meshes turns to be 200. On the occasion, an evaluation ratio and an evaluation ratio Accordingly, it is found from the comparison between the evaluation ratios that the binary signal with the lower threshold level is effective for better recognition processing. In the case of the mail article Q, it is effective as the threshold level is raised because the character and mark printed at the back face are also included in the binary signal as noise if the threshold level is low. For instance, the number e₁ of black meshes is 2400 and the number f₁ of noise meshes 500 when the threshold level is low. When the threshold level is made high, the number e₂ of black meshes turns to be 1500 while the number f₂ of noise meshes turns to be 100. On the occasion, the evaluation ratio and Accordingly, it is found from the comparison between the evaluation ratios that the binary signal with the higher threshold level results in better recognition processing. Now turning back to Fig. 1, the signal quality determination circuits 3, 4 and 5 deliver, consequently, evaluation ratios (f₁/e₁, f₂/e₂, f₃/e₃) with respect to a plurality of three binary signals B₁, B₂ and B₃, and send these ratios to a comparison circuit 11. The comparison circuit 11 compares three evaluation ratios f₁/e₁, f₂/e₂ and f₃/e₃ and delivers a selection signal to select one binary signal having the smallest evaluation ratio to a control circuit 12. Based on the selection signal sent from the comparison circuit 11, the control circuit 12 reads out the binary signal having the smallest evaluation ratio from the memory 6, and sends it to a recognition circuit 13. Based on the binary signal read out of the memory 6, the recognition circuit 13 conducts recognition of the scanned character. Fig. 2 shows a detailed block diagram of the isolated mesh extraction circuit 8 of Fig. 1. In the embodiment, the isolated mesh is extracted under the condition of a region of 3 x 3 meshes. In Fig. 2, the input binary signal B₁ (B₂, B₃) is supplied to a register section 14. This register section 14 is composed of shift registers 14 a , 14 b and 14 c having stages in the number corresponding to the number of meshes in the horizontal direction of the scanning area, and these registers are so arranged that the binary signal entering the left end of the shift register 14 a is shifted to the right while an output from the right end thereof turns to be an input of the subsequent shift register 14 b and that an output of the shift register 14 b turns likewise to be an input of the shift register 14 c . Then, as shown in the figure, stage signals C₁ to C₉ corresponding to 3 x 3 meshes are taken out of the respective consecutive three stages in the shift registers 14 a , 14 b and 14 c and supplied to an isolated (noise) mesh detection circuit 15. In response to the nine stage signals C₁ to C₉, the detection circuit 15 takes a logic output D as shown in the following equation. The detection output thereof signifies the detection of the isolated mesh. D = C₁·C₂·C₃·C₄· C ₅·C₆·C₇·C₈·C₉ + C ₁· C ₂· C ₃· C ₄#CDT#C₅· C ₆· C ₇· C ₈· C ₉ (1) In the equation (1), the mark C denotes an inverted output, and when "1" of the binary signal B denotes a black mesh and "0" thereof a white mesh, the former term of the equation signifies the detection of the isolated mesh of the white meshes surrounded by black meshes which is indicated by N₁ in Fig. 6, while the latter term thereof signifies the detection of the isolated mesh of the black meshes surrounded by white meshes which is indicated by N₂ in Fig. 6. Fig. 6 shows an example of binary signal constructed of a mesh matrix. Fig. 3 shows a second embodiment of the present invention. In this figure, a scanned signal from a scanner 1 therein is converted into a multiple-leveled ( n bits) digital signal by an A/D converter 16. When this digital signal delivered from the A/D converter 16 is represented by the multi-valued signal of n bits, m most significant (m ≦ n) bits from the MSB are stored in a memory 17. Respective m bits from the digital signal of n bits are to represent herein m binary signals which are produced by different threshold levels from one another, respectively. Next, the binary signals B₁′, B₂′, B₃′ and B₄′ in the number of m (four in this embodiment) are read out of the memory 17 and sent to four signal quality determination circuits 18, 19, 20 and 21. The four signal quality determination circuits 18 to 21 have the same construction as the signal quality determination circuits 3, 4 and 5 of Fig. 1, and they deliver evaluation ratios (f/e) with respect to the four binary signals B₁′ to B₄′ and transmit them to a comparison circuit 22. The comparison circuit 22 compares the four evaluation ratios (f/e) to determine the samllest one, therefrom, and sends a selection signal to a control circuit 23 to select one binary signal B′ corresponding to the smallest evaluated ratio. Based on this selection signal, the control circuit 23 reads a corresponding binary signal B′ out of the memory 17 and supplies it to a recognition circuit 13. Fig. 4 shows a third embodiment of the present invention. In Fig. 4, a scanned signal from a scanner 1 is sent to a binary processing circuit 24, in which two binary signals B₁″′ and B₂″′ each having a different characteristic from other are formed. The two binary signals B₁″′ and B₂″′ are sent to signal quality determination circuits 25 and 26, in which evaluation ratios (f/e) are calculated. The determination circuits 25 and 26 also have the same construction as the determination circuits 3, 4 and 5 of Fig. 1. The evaluation ratios (f/e) outputted from the signal quality determination circuits 25 and 26 are sent to a comparison circuit 27, which outputs a selection signal to select one binary signal having the smallest evaluation ratio (f/e). The embodiment of Fig. 4 differs from that of Fig. 1 in that the two binary signals B₁″′ and B₂″′ from the binary processing circuit 24 are supplied to recognition circuits 28 and 29, respectively, in which recognition processing are performed on the basis of the respective binary signals. The recognition results are sent from the recognition circuits 28 and 29 to a judging circuit 30. The judging circuit 30 also receives the selection signal from the comparison circuit 27. The judging circuit 30 operates in such a manner that, when the two recognition results delivered from the recognition circuits 28 and 29 are identical, this recognition result is determined as a final recognition result and that, when the two recognition results delivered from the recognition circuits 28 and 29 are different from each other, the recognition result corresponding to the binary signal having the smaller evaluation ratio (f/e) is determined as the final recognition result in response to the selection signal. Fig. 5 shows a fourth embodiment of the present invention. This embodiment differs from that of Fig. 4 in that it has a single recognition circuit 28 and a memory 31 instead of another recognition circuit. The recognition circuit 28 first receives a binary signal B₁″′ through a switch 32 and performs a recognition processing on the basis of the binary signal B₁″′ so as to deliver the recognition result to a judging circuit 30. While the binary signal B₁″′ is subjected to the recognition processing, another binary signal B₂″′ is stored in the memory 31. After the recognition processing of the binary signal B₁″′, the binary signal B₂″′ is read out of the memory 31 and, then, supplied to the recognition circuit 28 through the switch 32, and the recognition processing of the binary signal B₂″′ is performed therein. This recognition result is sent to the judging circuit 30. The judging circuit 30 operates in the same way as that in the embodiment of Fig. 4. Though the isolated mesh is dealt with as noise in the aforementioned embodiments, a projected mesh may also be extracted as a noise mesh. Such projected mesh is shown by a mesh N₃ in Fig. 6. A logic equation for extracting the projected mesh is as follows: E = C₁· C ₂· C ₃·C₄·C₅· C ₆·C₇· C ₈· C ₉ + C₁·C₂· C ₃#CDT#C₄· C ₅· C ₆·C₇·C₈· C ₉ (2) In the equation (2), the projected mesh of a black or white mesh in a region of 3 x 3 meshes is found in the horizontal direction. It is also possible to add a projected mesh in the vertical direction or others further thereto. As above described, the present invention enables the selection of an optimum binary signal by counting the number of meshes of isolated meshes as noise, thus enabling an accurate, stable character recognition apparatus.

Claims: An optical character recognition apparatus comprising: scanner means (1) for optically scanning a prescribed area to produce a scanned signal corresponding to a character contained in said prescribed scanning area; binary processing means (2) responsive to said scanned signal for producing a plurality of binary signals (B₁, B₂, B₃, B₁', B₂', B₃', B₄') each having a different quantization characteristic, each binary signal representing said prescribed scanning area consisting of a plurality of pixels arranged to form a matrix, a black pixel indicating a part of said character and a white pixel indicating a background part; black pixel number counting means (7) for counting the number of black pixels contained in each binary signal and for delivering a black pixel number (e₁) for each binary signal; isolated pixel number counting means (9) for counting the number of isolated pixels contained in each binary signal and for delivering an isolated pixel number (f₁) for each binary signal; ratio calculating means (10) for calculating the ratio (f₁/e₁) between said black pixel number (e₁) and said corresponding isolated pixel number (f₁) for each binary signal; comparison means (11) for determining an optimum binary signal from said plurality of binary signals (B₁, B₂, B₃, B₁', B₂', B₃', B₄') on the basis of comparison of the ratios calculated by said ratio calculating means (10); and recognition means (13) for recognizing said character contained in said prescribed scanning area on the basis of said optimum binary signal determined by said comparison means (11), characterized in that each of said isolated pixels corresponds to a noise pixel, said noise pixel being a white pixel (N₁) totally surrounded by black pixels or a black pixel (N₂) totally surrounded by white pixels and said isolated pixel number corresponds to a noise pixel number. An optical character recognition apparatus as claimed in claim 1, further comprising: storing means (6) for storing said plurality of binary signals, and means for reading out said optimum binary signal from said storing means in response to said comparison means (11). An optical character recognition apparatus as claimed in claim 1 or 2, wherein said binary processing means (2) includes converter means (16) for converting the output of said scanner means (1) into a digital signal, said digital signal being constructed by a first plurality (n) of bits; and means (17) for producing said plurality of binary signals (B₁', B₂', B₃', B₄') from said digital signal by delivering each of a second plurality (m) of bits constructing said digital signal. A character recognition apparatus comprising: scanner means (1) for scanning a character on a mail article with a predetermined scanning area to produce a scanned signal; binary processing means (24) coupled to said scanning means for producing a plurality of binary signals (B1", B2") from said scanned signal, said plurality of binary signals (B₁", B₂") being binary-coded under respective different quantization conditions, each of said binary signals (B₁", B₂") representing said predetermined scanning area consisting of a plurality of pixels arranged in a matrix form, a black pixel indicating a part of said character and a white pixel indicating a background part; black pixel number counting means (7) for counting the number of black pixels contained in each binary signal and for outputting a black pixel number (e₁) for each binary signal; isolated pixel number counting means (9) for counting the number of isolated pixels contained in each binary signal and for outputting a isolated pixel number (f₁) for each binary signal; ratio calculating means (10) for calculating the ratio (f₁/e₁) between said black pixel number (e₁) and said corresponding isolated pixel number (f₁) for each binary signal; and comparison means (27) for determining an optimum binary signal from said plurality of binary signals (B₁", B₂") on the basis of comparison of the ratios calculated by said ratio calculating means (10), characterized in that each of said isolated pixels corresponds to a noise pixel, said noise pixel being a white pixel (N₁) totally surrounded by black pixels or a black pixel (N₂) totally surrounded by white pixels, that said isolated pixel number corresponds to a noise pixel number, and that said apparatus further comprises recognition means (28, 29) for recognizing said character on said mail article on the basis of said plurality of binary signals (B1", B2") to produce a plurality of recognition results corresponding to said plurality of binary signals (B1", B2"), respectively; and selection means (30) responsive to said plurality of recognition results delivered from said recognition means (28, 29) and said comparison means (27) for selecting one recognition result corresponding to said optimum binary signal.

Inventors: KASUYA, SHIGENOBU C/O NEC CORPORATION, UMEDA, TETSUO C/O NEC CORPORATION
Applicants: NEC CORPORATION
Application year: 1987
Main classification: G06K9
IPC codes: G06T7, G06K9, H04N1