Segmentation and classification of mixed text/graphics/image documents

Kuo Chin Fan, Chi Hwa Liu, Yuan Kai Wang

研究成果: 雜誌貢獻期刊論文同行評審

45 引文 斯高帕斯(Scopus)

摘要

In this paper, a feature-based document analysis system is presented which utilizes domain knowledge to segment and classify mixed text/graphics/image documents. In our approach, we first perform a run-length smearing operation followed by the stripe merging procedure to segment the blocks embedded in a document. The classification task is then performed based on the domain knowledge induced from the primitives associated with each type of medium. Proper use of domain knowledge is proved to be effective in accelerating the segmentation speed and decreasing the classification error. The experimental study reveals the feasibility of the new technique in segmenting and classifying mixed text/graphics/image documents.

原文???core.languages.en_GB???
頁(從 - 到)1201-1209
頁數9
期刊Pattern Recognition Letters
15
發行號12
DOIs
出版狀態已出版 - 12月 1994

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