Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1023245904128
Title: Text retrieval from document images based on word shape analysis
Authors: Tan, C.L. 
Huang, W. 
Sung, S.Y. 
Yu, Z.
Xu, Y. 
Keywords: Document image analysis
Document vector
Similarity measure
Text retrieval
Issue Date: 2003
Source: Tan, C.L., Huang, W., Sung, S.Y., Yu, Z., Xu, Y. (2003). Text retrieval from document images based on word shape analysis. Applied Intelligence 18 (3) : 257-270. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1023245904128
Abstract: In this paper, we propose a method of text retrieval from document images using a similarity measure based on word shape analysis. We directly extract image features instead of using optical character recognition. Document images are segmented into word units and then features called vertical bar patterns are extracted from these word units through local extrema points detection. All vertical bar patterns are used to build document vectors. Lastly, we obtain the pair-wise similarity of document images by means of the scalar product of the document vectors. Four corpora of news articles were used to test the validity of our method. During the test, the similarity of document images using this method was compared with the result of ASCII version of those documents based on the N-gram algorithm for text documents.
Source Title: Applied Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/39403
ISSN: 0924669X
DOI: 10.1023/A:1023245904128
Appears in Collections:Staff Publications

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