전자공학회논문지B (Journal of the Korean Institute of Telematics and Electronics B)
- 제33B권10호
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- Pages.120-129
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- 1996
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- 1016-135X(pISSN)
문서영상의 에지 정보를 이용한 효과적인 블록분할 및 유형분류
An Efficient Block Segmentation and Classification of a Document Image Using Edge Information
초록
This paper presents an efficient block segmentation and classification using the edge information of the document image. We extract four prominent features form the edge gradient and orientaton, all of which, and thereby the block clssifications, are insensitive to the background noise and the brightness variation of of the image. Using these four features, we can efficiently classify a document image into the seven categrories of blocks of small-size letters, large-size letters, tables, equations, flow-charts, graphs, and photographs, the first five of which are text blocks which are character-recognizable, and the last two are non-character blocks. By introducing the clumn interval and text line intervals of the document in the determination of th erun length of CRLA (constrained run length algorithm), we can obtain an efficient block segmentation with reduced memory size. The simulation results show that the proposed algorithm can rigidly segment and classify the blocks of the documents into the above mentioned seven categories and classification performance is high enough for all the categories except for the graphs with too much variations.
키워드