Texture Image Segmentation using Fractional Discrimination Functions

This paper presents an approach to texture image segmentation using a family of fractional discrimination functions. In contrast to the conventional methods, the proposed functions provide uniform treatment of the existing functions and operators for selective feature extraction. The effectiveness of fractional discrimination functions for texture feature detection is demonstrated in the presence of noise and texture variation.This paper presents an approach to texture image segmentation using a family of fractional discrimination functions. In contrast to the conventional methods, the proposed functions provide uniform treatment of the existing functions and operators for selective feature extraction. The effectiveness of fractional discrimination functions for texture feature detection is demonstrated in the presence of noise and texture variation.
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Conference Title

1997 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT PROCESSING SYSTEMS, VOLS 1 & 2

Volume

Publisher URI

http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5482

DOI

https://doi.org/10.1109/ICIPS.1997.669132

Copyright Statement

© 1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Publication URI

http://hdl.handle.net/10072/19801

Collection

Conference outputs