Text locating in scene images for reading and navigation aids for visually impaired persons
Proceedings of the 12th international ACM SIGACCESS conference on Computers and accessibility
Improving computer vision-based indoor wayfinding for blind persons with context information
ICCHP'10 Proceedings of the 12th international conference on Computers helping people with special needs
Assistive text reading from complex background for blind persons
CBDAR'11 Proceedings of the 4th international conference on Camera-Based Document Analysis and Recognition
Text extraction from scene images by character appearance and structure modeling
Computer Vision and Image Understanding
Magnitude Sensitive Competitive Learning
Neurocomputing
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A new technique for color reduction of complex document images is presented in this article. It reduces significantly the number of colors of the document image (less than 15 colors in most of the cases) so as to have solid characters and uniform local backgrounds. Therefore, this technique can be used as a preprocessing step by text information extraction applications. Specifically, using the edge map of the document image, a representative set of samples is chosen that constructs a 3D color histogram. Based on these samples in the 3D color space, a relatively large number of colors (usually no more than 100 colors) are obtained by using a simple clustering procedure. The final colors are obtained by applying a mean-shift based procedure. Also, an edge preserving smoothing filter is used as a preprocessing stage that enhances significantly the quality of the initial image. Experimental results prove the method's capability of producing correctly segmented complex color documents where the character elements can be easily extracted as connected components. © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 14–26, 2009