NDLI: A density-based approach for text extraction in images

Content Provider	IEEE Xplore Digital Library
Author	Fang Liu Xiang Peng Tianjiang Wang Songfeng Lu
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan (Fang Liu; Xiang Peng; Tianjiang Wang; Songfeng Lu)
Abstract	In this paper we describe a new approach to distinguish and extract text from images with various objects and complex backgrounds. The goal of our approach is to present characters in images with clear background and without other objects. The proposed approach mainly includes two steps. Firstly, a density-based clustering method is employed to segment candidate characters by integrating spatial connectivity and color feature of characterspsila pixels. In most images, colors of pixels in one character are commonly non-uniform due to the noise. So a new histogram segmentation method is proposed in this step to obtain the color thresholds of characters. Secondly, priori knowledge and texture-based method are performed on the candidate characters to filter the non-characters. Experimental results show that the proposed approach has a good performance in character extraction rate.
Starting Page	1
Ending Page	4
File Size	387925
Page Count	4
File Format	PDF
ISBN	9781424421749
ISSN	10514651
DOI	10.1109/ICPR.2008.4761637
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Colored noise Image segmentation Clustering methods Image color analysis Gray-scale Clustering algorithms Histograms Optical character recognition software Computer science Pixel
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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