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
Extracting Text from WWW Images
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Flexible Web Document Analysis for Delivery to Narrow-Bandwidth Devices
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Automatic text detection and tracking in digital video
IEEE Transactions on Image Processing
Two Approaches for Text Segmentation in Web Images
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Multi-script and multi-oriented text localization from scene images
CBDAR'11 Proceedings of the 4th international conference on Camera-Based Document Analysis and Recognition
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This paper describes a new approach for the segmentation of characters in images on Web pages. In common with the authors' previous work in this subject, this approach attempts to emulate the ability of humans to differentiate between colours. In this case, pixels of similar colour are first grouped using a colour distance defined in a perceptually uniform colour space (as opposed to the commonly used RGB). The resulting colour connected components are then grouped to form larger (character-like) regions with the aid of a fuzzy propinquity measure. This measure expresses the likelihood for merging two components based on two features. The first feature is the colour distance in the L*a*b* colour space. The second feature expresses the topological relationship of two components. The results of the method indicate a better performance than the previous method devised by the authors and comparable (possibly better) performance to other existing methods.