23 February 2005 Content-based document enhancement by fuzzy clustering with spatial constraints
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Abstract
In this paper, we present a new system to segment and label the contents of scanned documents as either text or image, using a modified fuzzy c-means (FCM) algorithm. Each pixel is assigned a feature pattern extracted from the gray level distribution and computed at different scales. The invariant feature pattern is then assigned to a specific region using fuzzy logic. Our algorithm is formulated by modifying the objective function of the standard FCM algorithm to allow the labeling of a pixel to be influenced by the labels in its immediate neighborhood. 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.
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Mohamed Nooman Ahmed, Mohamed Nooman Ahmed, Brian E. Cooper, Brian E. Cooper, } "Content-based document enhancement by fuzzy clustering with spatial constraints", Proc. SPIE 5673, Applications of Neural Networks and Machine Learning in Image Processing IX, (23 February 2005); doi: 10.1117/12.585543; https://doi.org/10.1117/12.585543
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