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Method and system for image identification and identification result output

  • US 8,391,560 B2
  • Filed: 07/30/2009
  • Issued: 03/05/2013
  • Est. Priority Date: 04/30/2009
  • Status: Active Grant
First Claim
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1. A method for image identification and identification result output, comprising steps of:

  • providing an image to be identified comprising a region of interest thereon;

    acquiring a feature in the region of interest;

    determining a rotating angle based on at least one direction according to the feature; and

    comparing the image with sample images in a database corresponding to the rotating angle to obtain at least one identification result,wherein the step of comparing comprises the steps of;

    acquiring a feature image from the region of interest;

    acquiring the sample images in the database according to the at least one rotating angle, each sample image having respectively a standard image region and at least one non-standard image region, wherein the standard image region has pixels corresponding to a first feature value respectively, and the non-standard image region has pixels corresponding to a second feature value respectively;

    performing a normalized correlation matching calculation on a third feature value of each pixel in the feature image and the first feature value or the second feature value corresponding to each pixel in the plurality of sample images to obtain a similarity index of the feature image corresponding to the plurality of sample images respectively;

    collecting a plurality of similarity indexes with respect to the feature image compared with the plurality of sample images; and

    sorting the plurality of similarity indexes and outputting at least one of comparison results;

    wherein the step of acquiring the sample images comprise the steps of;

    determining the size of the sample images;

    providing in each of the sample images the standard image region;

    providing in each of the sample images the non-standard image region;

    storing the sample images in the database;

    observing the identification result after a plurality times of training; and

    modifying the standard image region and the non-standard image region in the sample images; and

    wherein the non-standard image region is formed by providing a pixel with the first feature value and the second feature value in the standard image region according to mis-identified characters in the standard image region.

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