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  1. University of Computer Studies, Yangon
  2. Conferences

Page Segmentation and Document Layout Analysis for Scanned Image by using Smearing Algorithm

http://hdl.handle.net/20.500.12678/0000003420
http://hdl.handle.net/20.500.12678/0000003420
ad9a3de2-2a0f-41fc-9948-0f1177dd7c8d
a6779e61-489a-4285-aafc-86cd3c680aa7
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psc2010paper psc2010paper (226).pdf (599 Kb)
Publication type
Article
Upload type
Publication
Title
Title Page Segmentation and Document Layout Analysis for Scanned Image by using Smearing Algorithm
Language en
Publication date 2010-12-16
Authors
Htun, Nay Win
Ko, Lin Min
Description
This paper presents a feature-based system which utilizes domain knowledge to segment and classify scanned image documents. Documents usually consists of a mixture of text and image. Text block possesses an interesting property that the x-profile or y-profile of text block is a periodic pattern. Image block possesses generate the connectivity histogram by summing the number of dark pixels with the same connectivity value. Initially, one-scan run-length smearing algorithm (RLSA) with block merging is proposed to segment the document. After segmentation process, the next task is to classify the segmented block. The classification task is then performed based on the rules induced from the features or primitives associated with each document. In this system, proper use of domain knowledge is proved to be effective in accelerating the segmentation speed and decreasing the classification error.
Keywords
one-scan run-length smearing, block merging, connectivity histogram, text block, image block
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1173
Journal articles
Fifth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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