Source: http://www.google.de/patents/US5617485
Timestamp: 2013-05-19 13:29:09
Document Index: 516783799

Matched Legal Cases: ['art 4', 'art 5', 'art 22', 'art 23', 'art 22', 'art 23', 'art 25', 'art 26', 'art 25', 'art 26', 'art 27', 'art 23', 'art 26', 'art 27', 'art 28', 'art 504', 'art 504', 'art 505', 'art 505', 'art 506', 'art 506', 'art 507', 'art 507', 'art 508', 'art 504', 'art 506', 'art 508', 'art 509', 'art 505', 'art 507', 'art 509', 'art 508', 'art 509', 'art 510', 'art 510', 'art 511', 'art 510', 'art 101', 'art 102', 'art 101', 'art 103', 'art 102', 'art 103', 'art 103', 'art 103', 'art 104', 'art 104']

Patent US5617485 - Image region segmentation system - Google PatenteSuche Bilder Maps Play YouTube News Gmail Drive Mehr » Erweiterte Patentsuche | Webprotokoll | Anmelden Erweiterte Patentsuche PatenteAn image region segmentation system includes a first detection part for detecting a candidate region for a text region within an image, a second detection part for detecting a white region within the image by carrying out a pattern matching of a matrix including a pixel of the image with predetermined...http://www.google.de/patents/US5617485?utm_source=gb-gplus-sharePatent US5617485 - Image region segmentation system Ver�ffentlichungsnummerUS5617485 APublikationstypErteilung Anmeldenummer08/485,553 Ver�ffentlichungsdatum1. Apr. 1997Eingetragen4. Apr. 1995 Priorit�tsdatum15. Aug. 1990 ErfinderKaoru ImaoSatoshi OhuchiUrspr�nglich Bevollm�chtigterRicoh Company, Ltd. US-Klassifikation382/176358/462382/194Internationale KlassifikationG06K9/20G06T5/00 UnternehmensklassifikationG06K9/00456H04N1/40062 Europ�ische KlassifikationG06K9/00L2H04N1/40LReferenzenPatentzitate (6)Nichtpatentzitate (4) Referenziert von (26)Externe LinksUSPTO USPTO-Zuordnung EspacenetImage region segmentation systemUS 5617485 A Zusammenfassung An image region segmentation system includes a first detection part for detecting a candidate region for a text region within an image, a second detection part for detecting a white region within the image by carrying out a pattern matching of a matrix including a pixel of the image with predetermined matrix patterns for a set of successive white pixels, and a discrimination part for detecting whether or not the candidate region detected by the first detection part is a text region by checking if a white region is detected in a neighborhood of the detected candidate region.
What is claimed is: 1. An image region segmentation system for discriminating a text region within an image, said system comprising: a) first detection means for detecting a candidate region for the text region within the image by outputting, for each pixel of the image included in the candidate region, a first signal indicating that said each pixel constitutes part of the candidate region for the text region; b) second detection means for detecting a white region including at least a group of successive white pixels within the image, by carrying out, for each of the pixels of the image, a pattern matching of: (i) a matrix of the pixels of the image including a reference pixel in the center of the matrix with (ii) predetermined matrix patterns, said second detection means including: 1) means for detecting whether a white region including at least a group of successive white pixels exists within the image at a predetermined distance from the reference pixel along a scanning line, and 2) means for supplying a second signal for each pixel of the image when the white region is detected to exist within the image at the predetermined distance from each said pixel; and c) discrimination means for detecting a text region within the image by determining that both the first signal and the second signal are simultaneously supplied by said first detection means and said second detection means with respect to each pixel of the image included in the detected text region.
BACKGROUND OF THE INVENTION The present invention relates generally to an image region segmentation system, and more particularly to an image region segmentation system for automatically discriminating a text region from an image in which a line image and a dot image (which includes a continuous-tone dot image and/or a screened halftone dot image) coexist. This system is applicable to digital copying machines and facsimile machines.
SUMMARY OF THE INVENTION Accordingly, it is a general object of the present invention to provide an improved image region segmentation system in which the above described problems are eliminated.
BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram showing a construction of an image reproducing system to which an image region segmentation system of the present invention is applied;
DESCRIPTION OF THE PREFERRED EMBODIMENTS First, a description will be given of an image reproducing system such as a facsimile machine, to which an image region segmentation system of the present invention is applied, by referring to FIG. 1. In FIG. 1, an image scanner 1 having a photoelectric conversion element such as a charge-coupled device (CCD) scans a document so that an analog halftone signal is generated from the scanned document, and an A/D converter 2 converts each signal from the image scanner 1 into a digital signal. This digital signal is, for example, a 8-bit digital signal. A LOG converter 3 carries out an optical density conversion process on each signal received from the A/D converter 2. A text image processing part 4 emphasizes an edge of an image by carrying out a sharpening process of each received image signal, and carries out a bilevel rendition process of each received image signal so that a binary signal is generated from an image signal for which the sharpening process is carried out. A picture image processing part 5 performs a smoothing process of each received image signal, and carries out a halftone image rendition process of the image signal by applying an ordered dither method or an error diffusion method to the image signal for which the smoothing process is carried out.
If a 3 the center of the matrix matches with one of eight standard patterns of black and non-black pixels shown in FIG. 3, the black pixel pattern matching part 22 detects a binary signal whose pixel forms a part of associated black pixels, and generates a signal indicating "one" with respect to each pixel of the received image signal. A counting part 23 increments the number of the received signals indicating "one" each time a signal indicating "one" is received from the pattern matching part 22. The number of the signals thus incremented shows the number of associated black pixels included in each 3 the associated black pixels is greater than a given reference number (which may be equal to, for example, 2), the counting part 23 generates a signal indicating "one" with respect to each pixel of the received signal.
Similarly, if a 3 binary signal in the center of the matrix matches with one of eight standard patterns of white and non-white pixels shown in FIG. 4, the white pixel pattern matching part 25 detects a binary signal whose pixel forms a part of associated white pixels, and generates a signal indicating "one" with respect to each pixel of the received signal. A counting part 26 increments the number of the received signals indicating "one" each time the signal indicating "one" is received from the pattern matching part 25. The number of the signals thus incremented shows the number of associated white pixels included in each 3 the associated white pixels is greater than a given reference number (for example, 2), the counting part 26 generates a signal indicating "one" with respect to each pixel of the received signal.
An AND part 27 generates a signal indicating conjunction between the signal from the counting part 23 and the signal from the counting part 26 with respect to each pixel of the received signal. In other words, if two or more associated black pixels and two or more associated white pixels coexist within the 3 signal in the center of the matrix, the AND part 27 generates a signal indicating "one". It is assumed that the pixel of the received signal in the center of the matrix is a candidate pixel which may form a part of a line image such as a character.
If the number of the candidate pixels in a 5 pixel of the received signal in the center of the matrix is greater than a given reference number, a discrimination part 28 judges that a block with a prescribed size including the pixel (or, the 5 including the pixel) is a text region within an image, and generates a signal indicating "one" for each pixel of the received signal. The text region detecting unit 61 detects a candidate region for a text region within an image, but the present invention is not limited to the embodiment shown in FIG. 2.
An associated black pixel pattern matching part 504 receives a three-level signal indicating a black pixel from the comparator 502, and detects whether or not each pixel of the received signal is closely associated with other black pixels in the neighborhood of the pixel of the received signal. If a 3 received signal in the center of the matrix matches with one of four 3 pixel pattern matching part 504 detects that the pixel in the center of the matrix is an associated black pixel closely associated with other neighborhood pixels, and generates a detection signal which is activated for the pixel of the received image signal. The above procedure is repeated with respect to each of the black pixels of three-level signals received from the comparator 502. The standard matrix patterns shown in FIG. 6 are used for detecting an associated black pixel within an image, and in these matrix patterns a shaded circle denotes a black pixel and cross-out mark denotes either a black pixel or a white pixel. As shown in FIG. 6, the associated black pixels are aligned straight in any of up/down, right/left and inclined directions, which feature is utilized for the pattern matching of associated black pixels.
An associated white pixel pattern matching part 505 receives a three-level signal indicating a white pixel from the comparator 503, and detects whether or not each pixel of the received signal is closely associated with other white pixels in the neighborhood of the pixel of the received signal. If a 3 received signal in the center of the matrix matches with one of four four 3 pixel pattern matching part 505 detects that the pixel in the center of the matrix is an associated white pixel closely associated with other neighborhood pixels, and generates a detection signal which is activated for the pixel of the received image signal. The above procedure is repeated with respect to each of the white pixels of three-level signals received from the comparator 503. The standard matrix patterns shown in FIG. 7 are used for detecting an associated white pixel within an image, and in these matrix patterns, a blank circle denotes a white pixel and a cross-out mark denotes either a black pixel or a white pixel. As shown in FIG. 7, the associated white pixels are aligned straight in any of up/down, right/left and inclined directions, which feature is utilized for the pattern matching of associated white pixels.
A screened black pixel pattern matching part 506 detects whether or not each black pixel of the received signals received from the comparator 502 forms part of a screened halftone black dot image within an image. If a 3 the center of the matrix matches with one of four 3 matrix patterns shown in FIG. 8, the screened black pixel pattern matching part 506 detects that the pixel in the center of the matrix forms part of a screened halftone black dot image, and generates a detection signal which is activated for the pixel of the received image signal. The above procedure is repeated with respect to each of the black pixels of three-level signals received from the comparator 502. The standard matrix patterns shown in FIG. 8 are used for detecting a screened halftone black pixel within an image, and in these matrix patterns, a blank circle denotes a white pixel and a shaded circle denotes a black pixel.
A screened white pixel pattern matching part 507 detects whether or not each white pixel of the received signals received from the comparator 503 forms part of a screened halftone white dot image within an image. If a 3 the center of the matrix matches with one of four 3 matrix patterns shown in FIG. 9, the screened white pixel pattern matching part 507 detects that the pixel in the center of the matrix forms part of a screened halftone white dot image, and generates a detection signal which is activated for the pixel of the received image signal. The above procedure is repeated with respect to each of the white pixels of three-level signals received from the comparator 503. The standard matrix patterns shown in FIG. 9 are used for detecting a screened halftone white pixel within an image, and in these matrix patterns a blank circle denotes a white pixel and a shaded circle denotes a black pixel.
With respect to each black pixel of the received image signals, a black bilevel pixel discrimination part 508 checks whether or not the pixel of the received image signal is an active black pixel that is judged as being an associated black pixel by the pattern matching part 504 and is judged as not being a screened halftone black pixel by the pattern matching part 506. Then, the black bilevel pixel discrimination part 508 detects whether or not the number of such active black pixels included in a pixel matrix with a prescribed size (for example, a 3 predetermined reference value (for example, 2). If the number of the active pixels in the matrix is greater than the reference number, it is judged that the pixel in the center of the matrix is a black bilevel pixel which forms part of a line image such as a character. For example, if two or more active black pixels are included in a 3 is judged that the pixel in the center of the matrix is a black bilevel pixel.
Similarly, with respect to each black pixel of the received image signals, a white bilevel pixel discrimination part 509 checks whether or not the pixel of the received image signal is an active white pixel that is judged as being an associated white pixel by the pattern matching part 505 and is judged as not being a screened halftone white pixel by the pattern matching part 507. Then, the white bilevel pixel discrimination part 509 detects whether or not the number of such active white pixels included in a pixel matrix with a prescribed size (for example, a 3 greater than a predetermined reference value (for example, 2). If the number of the active pixels in the matrix is greater than the reference number, it is judged that the pixel in the center of the matrix is a white bilevel pixel which forms part of a line image such as a character. For example, if two or more active white pixels are included in a 3 pixel matrix, it is judged that the pixel in the center of the matrix is a white bilevel pixel.
Based on the results of the detections by the black bilevel pixel discrimination part 508 and the white bilevel pixel discrimination part 509, if the number of black bilevel pixels in a matrix with a prescribed size (for example, a 5 reference value (for example, 2) and the number of white bilevel pixels in the same matrix is greater than the reference value, it is judged that the pixel in the center of the matrix is a bilevel pixel which forms part of a line image such as a character. For example, if it is found that two or more black bilevel pixels and two or more white bilevel pixels coexist in a 5 matrix is a bilevel pixel which forms part of a line image. An AND part 510 carries out this judgment with respect to each pixel of the received image signal as described above, but the discriminated bilevel pixel is limited to pixels on boundaries between a black area and a white area of a line image. In other words, the internal pixels of a line image cannot be detected by the AND part 510. A dilatation part 511 carries out a dilatation of the pixels of the received signals from the AND part 510, so that the internal pixels of a line image are also checked as to whether the pixels are bilevel pixels of a line image. Therefore, according to the present invention, it is possible to accurately discriminate a text region from an image, the text region including bilevel pixels on boundaries of a line image and the internal bilevel pixels of the line image. In the text region discrimination described above, a screened halftone pixel within the image is detected.
FIG. 10 shows a construction of a white region detecting unit of the image region segmentation system according to the present invention. A white region refers to a region of an image in which a set of successive white pixels having a predetermined matrix size (for example, a 1 size or a 5 pixel. The white region detecting unit 62 detects a white region within an image in the following manner. In FIG. 10, a MTF correction part 101 carries out a sharpening process of an image signal, a bilevel rendition part 102 carries out a bilevel image rendition process of an image signal from the MTF correction part 101 by comparing an intensity level of the image signal with a predetermined threshold level, and a white pixel set pattern matching part 103 receives a two-level signal indicating either a white pixel or a non-white pixel from the bilevel rendition part 102.
FIG. 11 shows matrix patterns of a white pixel set including successive white pixels. The matrix patterns are a 1 white pixels aligned in a horizontal direction and a 5 pattern of five white pixels aligned in a vertical direction. The white pixel set pattern matching part 103 detects a white pixel set in the neighborhood of a subject pixel within an image by carrying out a pattern matching of a pixel matrix with the matrix patterns shown in FIG. 11. If a pixel matrix including a subject pixel in the center of the matrix matches with one of the matrix patterns shown in FIG. 11, the white pixel set pattern matching part 103 judges that the pixel in the center of the matrix is an active pixel. The matrix described above is, for example, a 5 matching part 103, a dilatation part 104 checks the number of active pixels included the the above matrix having the detected pixel in the center of the matrix. If at least one active pixel is detected in the matrix, the dilatation part 104 judges that the matrix is a white region within an image, and generates a signal indicating that the pixel forms part of the white region within the image.
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