Fuzzy C-Mean : A statistical feature classification of text and image segmentation method

Fuzzy C-Mean : A statistical feature classification of text and image segmentation method
วิธีการแบ่งแยกข้อความและภาพด้วยวิธี Fuzzy C-Mean โดยใช้ลักษณะสำคัญทางสถิติ

Somporn Chuai-aree, D. of Mathematics and Computer Sci., F. of Sci. and Tech., PSU.
Suchada Siripant, Assoc. Prof., AVIC, D. of Mathematics, Chulalongkorn U., Bangkok
Chidchanok Lursinsap, Prof., AVIC, D. of Mathematics, Chulalongkorn U., Bangkok
Peraphon Sophatsatit, Asst. Prof., AVIC, D. of Mathematics, Chulalongkorn U., Bangkok
Corresponding e-mail : csomporn@falcon.sat.psu.ac.th

Presented : International Conference on Intelligent Technologies, December 13-15, 2000, pp. 279-284, Assumption University Bangkok, Thailand
Key words : segmentation, clustering, statistical classification

Classification of text and image using statistical features (mean and standard deviation of pixel color values) is found to be a simple yet powerful method for text and image segmentation. The features constitute a systematic structure that segregates one from another. We identified this segregation in the form of class clustering by means of Fuzzy C-Mean method, which determined each cluster location using maximum membership defuzzification and neighborhood smoothing techniques. The method can then be applied to classify text, image, and background areas in optical character recognition (OCR) application for elaborated open document systems.

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