Please use this identifier to cite or link to this item: http://148.72.244.84:8080/xmlui/handle/xmlui/6690
Title: Unsupervised Image Classification Technique for Lung Diseases Diagnosis using Fuzzy C-mean Clustering algorithm and Q-Matrix
Authors: Alyaa Hussein Ali
Keywords: keyword: lung dieses, Q-matrix, Gabor texture features , FCM, X-ray Images .
Issue Date: 2016
Abstract: The study aim to classify three x-ray lung images depending on the fuzzy c- mean classifier process and on the Q-matrix. The fuzzy c-mean (FCM) is unsupervised process helps to gather the pixel which carry the same features in one or in two classes. The Qmatrix is gray level matrix based on some features which may be used to help the user in identifying the identity of the texture. Also, Gabor texture features has been used to calculate the textural statistical features in this search five cases have been used which are ( Cancer, Echinococcosis, Lymphatic, Pneumonia, Tuberculosis)
URI: http://148.72.244.84:8080/xmlui/handle/xmlui/6690
ISSN: 2222-8373
Appears in Collections:مجلة ديالى للعلوم الاكاديمية / Academic Science Journal (Acad. Sci. J.)

Files in This Item:
File Description SizeFormat 
25-38 E.pdf930.91 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.