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	Document image retrieval based on multi-density features
	Hu Zhilan ; Lin Xinggang ; Yan Hong
	2010-05-06 ; 2010-05-06
关键词	Practical Theoretical or Mathematical Experimental/ document image processing feature extraction image reconstruction image resolution image retrieval optical character recognition visual databases/ document image retrieval multidensity feature extraction document image database layout reconstruction optical character recognition OCR preprocessing skew correction marginal noise image resolution/ B6135E Image recognition C1250B Character recognition C1250M Image recognition C7250R Information retrieval techniques C6130D Document processing techniques C5260B Computer vision and image processing techniques C6160S Spatial and pictorial databases
中文摘要	The development of document image databases is challenging document image retrieval techniques. Traditional layout reconstructed-based methods rely on high quality document images and can only deal with several widely used languages. The complexity of document layouts greatly hinter layout analysis-based approaches. This paper describes a multi-density feature-based algorithm for binary document images, which is independent of optical character recognition (OCR) or layout analyses. The text area is extracted after preprocessing including skew correction and marginal noise removal. Then the aspect ratio and multi-density features are extracted from the text area to select the best candidates from the document image database. Experimental results show that this approach is simple with loss rates less than 2% and can efficiently analyze images with different resolutions and different input systems. The system is also robust to noise due to such as notes and complex layouts.
语种	中文 ; 中文
出版者	Tsinghua Univ. Press ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/11953]
专题	清华大学
推荐引用方式 GB/T 7714	Hu Zhilan,Lin Xinggang,Yan Hong. Document image retrieval based on multi-density features[J],2010, 2010.
APA	Hu Zhilan,Lin Xinggang,&Yan Hong.(2010).Document image retrieval based on multi-density features..
MLA	Hu Zhilan,et al."Document image retrieval based on multi-density features".(2010).

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