In this paper, we propose a method of character extraction for scene images based on identification of a local target area and adaptive thresholding. The proposed extraction method is performed as follows: A scene image is resolved into a lightness image and a saturation image using a HSL transform. Vertical and horizontal edge images are made from these two images, and these edge images are binarized and thinned. The corresponding prominent features in the saturation and lightness images are detected using the Hough transform. A region between straight vertical lines is then extracted as a signboard region candidate in reference to the edge histogram. The extracted signboard region candidate is binarized using a threshold value determined by adaptive thresholding for each character region in the signboard region. The binary image containing extracted characters is then analyzed and the linear region containing the most character strings is identified as the character string region. This technique was applied to 100 scene images in order to verify the reliability of character extraction. Of the 450 characters in all the images, 438 were extracted correctly, representing a 97.3% successful recognition rate. Correct character strings were extracted in 98 of the 100 strings examined.
In this paper, we propose a multi-expert seal imprint verification system. The system has been specifically designed for applications in the Japanese bankcheck processing. A difficult problem encountered in automatic seal imprint verification is that the system is required an extremely low error rate despite of using a small number of reference data for training. To conquer this problem, it combines two different algorithms for seal imprint verification.A seal imprint is first extracted from bankcheck image based on color features. The first verification algorithm is based on a method using local and global features of seal imprint. The second algorithm uses a special correlation based on a global approach. The two algorithms are combined in the multi-expert system by a voting strategy.Experimental results showed that the combination of the two algorithms improves significantly the verification performance both on "false-acceptance error rate" and "false-rejection error rate".
In this paper we propose a new method to extract separately filled-in items from Japanese bank-checks based on prior knowledge about their color characteristics and layout. We have analyzed the bank-check characteristics and proposed a model that can be used to extract the filled-in items applicable to any Japanese bank-checks. The areas where the filled-in item is supposed to appear are first extracted through a template. Then the filled-in characters and seal imprints are extracted on the basis of their color characteristics in HSV color space. The results of testing experiments show that this extraction method is capable of extracting the filled-in items from most Japanese bank-checks.
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