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    METHOD AND DEVICE FOR REMOVING RULED LINE
    3.
    发明专利
    METHOD AND DEVICE FOR REMOVING RULED LINE 失效

    公开(公告)号：JP2000322510A

    公开(公告)日：2000-11-24

    申请号：JP11931599

    申请日：1999-04-27

    Applicant: IBM

    Inventor： KATO MAKOTO ,  TAKAHASHI HIROYASU

    IPC: G06K9/20 ,  G06K9/34 ,  G06K9/40 ,  G06T3/60 ,  G06T5/00 ,  G06T7/00 ,  G06T7/60

    Abstract: PROBLEM TO BE SOLVED: To remove a ruled line at high speed and to restore a character part erased together at high speed by detecting the black run of a lateral ruled line and storing it as a run length table for each longitudinal position. SOLUTION: The black run is detected from an image area and for each longitudinal position of the detected black run, the run length table composed of a lateral starting point and a length from the starting point is prepared (S1). The black run of the length equal to or greater than a threshold value is selected and removed from an image (S2). Residual noise with the mark of the ruled line is erased (S3). Two components having possibility to be longitudinally divided by removal are simply coupled (S4). The erased black run is reproduced on the image in the same size as an input image (S5). ANDed for each pixel and only the erased character part overlapped with the ruled line is left (S6). The ruled line removed image and the erased black pixel in the character part are ORed for each pixel and synthesized and a part erased together with the ruled line is restored (S7).

    Character recognition result output device, character recognition device, its method and program
    4.
    发明专利
    Character recognition result output device, character recognition device, its method and program 有权
    字符识别结果输出设备，字符识别设备，其方法和程序

    公开(公告)号：JP2005309608A

    公开(公告)日：2005-11-04

    申请号：JP2004123277

    申请日：2004-04-19

    Applicant: Internatl Business Mach Corp ,  インターナショナル・ビジネス・マシーンズ・コーポレーションInternational Business Maschines Corporation

    Inventor： KATO MAKOTO ,  ARIMA TOSHIMICHI ,  SUMIKAWA MICHITOSHI

    IPC: G06K9/03 ,  G06K9/46 ,  G06K9/50 ,  G06K9/62

    CPC classification number: G06K9/50 ,  G06K2209/01

    Abstract: PROBLEM TO BE SOLVED: To reduce the burden of an operator by displaying character images similar in letter shape whose typefaces are similar collectively in a confirmation screen where the character images in the same category are arranged, thereby improving the operation efficiency of confirming/correcting recognition results by the operator. SOLUTION: This output mechanism of a character recognition device is provided with: a category classifying part 20 for classifying the image data of characters being the target of the character recognition processing for every character(category) recognized by the character recognition processing; a clustering processing part 30 for calculating featured values related with the shapes of the characters included in the image data in each category classified by the category classifying part 20, and for classifying the image data into one or more clusters based on the featured values; and a picture generating part 50 for generating and displaying the confirmation picture on which the image data are displayed for every cluster classified by the clustering processing part 30. COPYRIGHT: (C)2006,JPO&NCIPI

    Abstract translation: 要解决的问题：通过在同一类别的字符图像的确认画面中显示与字体形状相似的字符形状的字符图像来减轻操作者的负担，从而提高确认的操作效率 /操作员校正识别结果。 解决方案：字符识别装置的输出机构具有：类别分类部分20，用于对通过字符识别处理识别的每个字符（类别）对作为字符识别处理的目标的字符的图像数据进行分类; 聚类处理部分30，用于计算与由类别分类部分20分类的每个类别中包括在图像数据中的字符的形状相关的特征值，并且基于特征值将图像数据分类成一个或多个聚类; 以及图像生成部50，用于生成并显示对于通过聚类处理部30分类的每个聚类显示图像数据的确认图像。（C）2006，JPO＆NCIPI

    METHOD AND DEVICE FOR PATTERN RECOGNITION BY NEURAL NETWORK
    5.
    发明专利
    METHOD AND DEVICE FOR PATTERN RECOGNITION BY NEURAL NETWORK 失效

    公开(公告)号：JPH0765165A

    公开(公告)日：1995-03-10

    申请号：JP21138693

    申请日：1993-08-26

    Applicant: IBM JAPAN

    Inventor： FUJITA MASAYUKI ,  TOYOKAWA KAZUHARU ,  KATO MAKOTO

    IPC: G06K9/66 ,  G06T7/00

    Abstract: PURPOSE:To improve the recognition rate of the pattern recognizing device which uses the neural network. CONSTITUTION:The section (0,1) of output of the neural network is equally divided into M (M: integer larger than 2) and the number or frequencies of correct answer and wrong answer pattern data included in an (i)th section [(i-1)/M, i/M] are denoted as mu1i and mu0i (where i=1 to M). At this time, when this netowrk grants an output included in the (i)th section for unknown pattern data, the likelihood P1i that this pattern is in this category is stored as an equation P1i=(mu1i+1)/(mu1i+mu01+2) and a likelihood conversion table to be outputted. Then a likelihood converter inputs a value included in the (i)th section [(i-1)/M, i/M] when it is outputted from the neural network and outputs P1i as what is called normalized likelihood.

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