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Image Segmentation Based on New Modification on Normalized-Cut Algorithm
Author(s) -
Khalil Alsaif
Publication year - 2010
Publication title -
maǧallaẗ al-rāfidayn li-ʿulūm al-ḥāsibāt wa-al-riyāḍiyyāẗ/˜al-œrafidain journal for computer sciences and mathematics
Language(s) - English
Resource type - Journals
eISSN - 2311-7990
pISSN - 1815-4816
DOI - 10.33899/csmj.2010.163907
Subject(s) - canny edge detector , artificial intelligence , deriche edge detector , image (mathematics) , algorithm , filter (signal processing) , wavelet , transformation (genetics) , computer vision , enhanced data rates for gsm evolution , computer science , image segmentation , pattern recognition (psychology) , segmentation , digital image , edge detection , mathematics , image processing , chemistry , biochemistry , gene
In this research, Normalized Cut algorithm was studied to segments any type of digital images which was widely used recently. In this paper wavelet transformation, and high-high frequency components which hold the edges of the image will be used to replace classical high frequency filters of the old techniques achieved by the normalized cut algorithm ( which used CANNY filter for edge detection). When the new modification of the proposed algorithm applied on the different type of digital images (medical, aerial and natural images) after crossover the CANNY filter by the wavelet high-high coefficients, a very efficient segments were found much better than the segments got before, in addition to a deep information can be seen if the selected segment is projected on the original image to be recognized.

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