Human factors for color display systems: concepts, methods, and research
Color and the computer
DL '97 Proceedings of the second ACM international conference on Digital libraries
Page segmentation using the description of the background
Computer Vision and Image Understanding - Special issue on document image understanding and retrieval
Locating and Recognizing Text in WWW Images
Information Retrieval
Flexible Web Document Analysis for Delivery to Narrow-Bandwidth Devices
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Web Document Analysis: Challenges and Opportunities
Web Document Analysis: Challenges and Opportunities
A framework for the assessment of text extraction algorithms on complex colour images
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
CCIW'11 Proceedings of the Third international conference on Computational color imaging
CCIW'11 Proceedings of the Third international conference on Computational color imaging
A text reading algorithm for natural images
Image and Vision Computing
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There is a significant need to extract and analyse the text in images on Web documents, for effective indexing, semantic analysis and even presentation by non-visual means (e.g., audio). This paper argues that the challenging segmentation stage for such images benefits from a human perspective of colour perception in preference to RGB colour space analysis. The proposed approach enables the segmentation of text in complex situations such as in the presence of varying colour and texture (characters and background). More precisely, characters are segmented as distinct regions with separate chromaticity and/or lightness by performing a layer decomposition of the image. The method described here is a result of the authors' systematic approach to approximate the human colour perception characteristics for the identification of character regions. In this instance, the image is decomposed by performing histogram analysis of Hue and Lightness in the HLS colour space and merging using information on human discrimination of wavelength and luminance.