Breast cancer is second most dangerous disease in the world after the lung cancer among women. Because ofthis reason, breast cancer detection is most focused area by many researchers. Digital mammographic images andadvanced techniques are required by many researchers for developing Computer aided detection (CAD) for breastcancer detection. This study describes the recent advances in image processing and machine learning techniques forbreast cancer detection. The study shows that Local Binary Pattern method used for feature extraction and Supportvector machine for classification as foremost technique used for breast cancer detection. The comparative study ofliterature work summarizes the effectiveness of different approach used by researchers for breast cancer detection.