The aim of this work is to efficiently detect breast cancer at an early stage and reduce the death rates of women. The purpose of this work is to identify the tumor present in the breast region of mammogram image as benign or malignant as these images are generally of low quality and sometimes radiologists need to seek second opinion to come to the conclusion that cancer is present. The image processing procedure is applied to detect breast cancer from mammographic ROI image. Earlier doctors used MRI, CT-scan, Ultrasound techniques to detect breast cancer, using which it was difficult to identify cancerous tumour at an early stage. The proposed methodology uses mammography technique to identify the tumor present in the breast region. The discrete wavelet and Contourlet transforms are used to decompose the given gray-scale image. The statistical and textual features are being extracted from the coefficients of spatial domain along with frequency domain values. The classification of mammographic ROI image is performed using support vector and artificial neural classifiers. The tool used in this work is Matlab. This work is recommended to study for all those working on breast cancer area of an image processing domain.