Texture features are playing major role now-a-days for the analysis of medical images. With the help of texture features extraction and classification, we can differentiate between pathological and healthy issues in various organs. In this paper, we have formed gray level cooccurrence matrix (GLCM) for MR brain images. Then, we have extracted Haralick texture features and then used support vector machine (SVM) using Gaussian radical basis function for classification between malignant and healthy brain. The performance of various texture features are compared in terms of percentage accuracy for the correct classification of images.
|Original language||English (US)|
|Number of pages||8|
|Journal||Far East Journal of Electronics and Communications|
|Publication status||Published - Jan 1 2016|
ASJC Scopus subject areas
- Computer Science(all)
- Electrical and Electronic Engineering