期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：5
页码：259-268
DOI：10.14257/ijsip.2016.9.5.23
出版社：SERSC
摘要：In the present work, a computer aided classification system has been proposed for classification of mammogram images into normal, benign and cancer classes. The work has been carried out on thirty Digital Database for Screeningmammography(DDSM) cases consisting of 10 normal, 10 benign and 10 cancer images. The regions of interest (ROI) have been extracted from the right Medio Lateral Oblique (RMLO) part of the mammogram. We extracted 256×256 pixel size ROI from each case. Texture descriptors based on gray level co-occurrence method by varying the value of inter pixel distance 'd' from 1 to 8 have been used. The SVM classifier has been used for the classification task. The result of the study indicates that GLCM mean and range features computed at d=1 yield the maximum overall classification accuracy of 75% and 65 % respectively
关键词：DDSM images; Gray level co-occurrence matrix and Support vector ; machine
