Author/Authors :
DEMIRHAN, Ayse Gazi Üniversitesi - Teknik Egitim Fakültesi - Elektronik-Bilgisayar Egitimi Bölümü, Turkey , GÜLER, Inan Gazi Üniversitesi - Teknik Egitim Fakültesi - Elektronik-Bilgisayar Egitimi Bölümü, Turkey
Title Of Article :
IMAGE SEGMENTATION USING SELF-ORGANIZING MAPS AND GRAY LEVELCO-OCCURRENCE MATRICES
شماره ركورد :
16367
Abstract :
Image segmentation is the separation of an image into segments called classes or subsets, according to one or more characteristics or features, and enhancing areas of interest by separating them from the background and other areas. Image segmentation is the most difficult stage in image processing. The success of subsequent image analysis and related applications depends greatly on the success of image segmentation. In this study images were segmented using self-organizing map (SOM) networks, and gray level co-occurrence matrices (GLCM). The performances of these methods on image segmentation were evaluated. It is seen that these methods showed %90 success on image segmentation applications.
From Page :
285
NaturalLanguageKeyword :
Image segmentation , self , organizing maps , gray level co , occurrence matrix
JournalTitle :
Journal Of The Faculty Of Engineering an‎d Architecture Of Gazi University
To Page :
291
Link To Document :
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