• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.65-73
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• 2013

As the advent of the digital age, documents are often scanned to be archived or to be transmitted over the network. The largest proportion of documents is texts and the next is seal images indicating the author of the documents. While a lot of research has been conducted to recognize texts in scanned documents and commercialized text recognizing products are developed as highlighted the importance of the scanned document, information about seal images is discarded. In this paper, we study how to extract the seal image area from the color or black and white document containing the seal image and how to save the seal image. We propose a preprocessing step to remove other components except for the candidate outlines of the seal imprint from scanned documents and a method to select the final region of interest from these candidates by using the feature of seal images. Also in case of a seal imprint overlapped with texts, the most similar image among those stored in the database is selected through the template matching process. We verify the implemented system for a various type of documents produced in schools and analyze the results.

• Journal of the Korea Society of Computer and Information
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• v.3 no.3
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• pp.17-22
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• 1998

As time goes on, that becomes an issue still more for truth from error of a seal in electronic settlement , or in important document in the field of image recognition. But on the other hand image treatment method of a seal have has the weakness until now. It makes indistinct distinction of part that light and darkness is changed sharply as the edge of things. So it has difficult that edge detection is extracted. In this paper, I investigated the pixel in a specific area by using enhanced smothing method and searched a value of frquent occurrence. The value of pixel is substituted and edge detection is extracted. After then it could be classified rightly according as viligence test is dynamically changed. I applied conventional of Yager's generated intersection operator among fuzzy logic operator in ART1 learning Algorithm. Application of suggested ART1 learning algorithm, it results in improved image recognition rate than a case of using the conventional ART1 algorithm

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.31-37
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• 2009

This paper casts an application of an extended fuzzy integral on the selective extraction of color clusters characterized by a particular color hue from color document images. Despite of the negative role of fuzzy integral, the presented approach attains the detection of the seals through the neighborhood information via the center of area method. The conventional fuzzy integral evaluates the negative aspects of the importance about the items by min operator, which result in the discontinuous parts of seals. In an attempt to cope with the drawback our approach considers the integral aspects via the center of area method, which results in the robustness of the images. Finally, the framework is successfully tested on a data set formed by documents from a real application for the detection.