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Proceedings Paper

Segmentation and enhancement of digital copies using a new fuzzy clustering method
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Paper Abstract

In this paper, we introduce a new system to segment and label document images into text, halftoned images, and background using a modified fuzzy c-means (FCM) algorithm. Each pixel is assigned a feature vector, extracted from edge information and gray level distribution. The feature pattern is then assigned to a specific region using the modified fuzzy c-means approach. In the process of minimizing the new objective function, the neighborhood effect acts as a regularizer and biases the solution towards piecewise-homogeneous labelings. Such a regularization is useful in segmenting scans corrupted by scanner noise.

Paper Details

Date Published: 17 February 2006
PDF: 8 pages
Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 60641C (17 February 2006); doi: 10.1117/12.643243
Show Author Affiliations
Mohamed Nooman Ahmed, Lexmark International, Inc. (United States)
Brian E. Cooper, Lexmark International, Inc. (United States)


Published in SPIE Proceedings Vol. 6064:
Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Nasser M. Nasrabadi; Edward R. Dougherty; Jaakko T. Astola; Syed A. Rizvi; Karen O. Egiazarian, Editor(s)

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