CLASSIFICATION OF DOCUMENT BLOCKS USING DENSITY FEATURE AND CONNECTIVITY HISTOGRAM

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Computer Science and Information Engineering > journal & Dissertation > Item 987654321/29223

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Title:	CLASSIFICATION OF DOCUMENT BLOCKS USING DENSITY FEATURE AND CONNECTIVITY HISTOGRAM
Authors:	FAN,KC;WANG,LS
Contributors:	資訊工程研究所
Date:	1995
Issue Date:	2010-06-29 20:16:47 (UTC+8)
Publisher:	中央大學
Abstract:	In this paper, we present a document block classification algorithm to automatically classify different types of blocks embedded in a document image. Two kinds of features, density feature and connectivity histogram, are devised to achieve the classification goal. In our approach, segmented document blocks are first classified into text and non-text blocks via the density feature. Then, the connectivity histogram is utilized to further classify non-text blocks into image and graphics blocks. Experimental results reveal the feasibility of the new technique in classifying document blocks.
Relation:	PATTERN RECOGNITION LETTERS
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] journal & Dissertation

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