DocumentCode :
2020856
Title :
Character-Stroke Detection for Text-Localization and Extraction
Author :
Subramanian, Krishna ; Natarajan, Prem ; Decerbo, Michael ; Castanon, David
Volume :
1
fYear :
2007
fDate :
23-26 Sept. 2007
Firstpage :
33
Lastpage :
37
Abstract :
In this paper, we present a new approach for analysis of images for text-localization and extraction. Our approach puts very few constraints on the font, size and color of text and is capable of handling both scene text and artificial text well. In this paper, we exploit two well-known features of text: approximately constant stroke width and local contrast, and develop a fast, simple, and effective algorithm to detect character strokes. We also show how these can be used for accurate extraction and motivate some advantages of using this approach for text localization over other color-space segmentation based approaches. We analyze the performance of our stroke detection algorithm on images collected for the robust-reading competitions at ICDAR 2003.
Keywords :
handwritten character recognition; image colour analysis; image segmentation; text analysis; artificial text; character-stroke detection; color-space segmentation; image analysis; text localization; text-extraction; text-localization; Algorithm design and analysis; Content based retrieval; Detection algorithms; Image analysis; Image retrieval; Image segmentation; Layout; Performance analysis; Robustness; Storage automation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2007. ICDAR 2007. Ninth International Conference on
Conference_Location :
Parana
ISSN :
1520-5363
Print_ISBN :
978-0-7695-2822-9
Type :
conf
DOI :
10.1109/ICDAR.2007.4378671
Filename :
4378671
Link To Document :
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