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- E-ISSN2982-6292
A Keyword Matching for the Retrieval of Low-Quality Hangul Document Images
A Keyword Matching for the Retrieval of Low-Quality Hangul Document Images
박상철 (삼성메디슨)
김수형 (전남대학교)
Abstract
It is a difficult problem to use keyword retrieval for low-quality Korean document images because these include adjacent characters that are connected. In addition, images that are created from various fonts are likely to be distorted during acquisition. In this paper, we propose and test a keyword retrieval system, using a support vector machine (SVM) for the retrieval of low-quality Korean document images. We propose a keyword retrieval method using an SVM to discriminate the similarity between two word images. We demonstrated that the proposed keyword retrieval method is more effective than the accumulated Optical Character Recognition (OCR)-based searching method. Moreover, using the SVM is better than Bayesian decision or artificial neural network for determining the similarity of two images.
- keywords
- Low-Quality Korean Document Keyword Retrieval, SVM, OCR, Digital Library
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