Mammography is one of the most widely used methods for breast cancer detection. The technique and theory of image processing and pattern recognition can be used for mammogram analysis. The analytical results can assist radiologist in finding missed tumors and identifying false positive tissues, leading to low false negative rate and false positive rate. The method using image processing should simulate the mammogram interpretation of the radiologist. Thus, the breast cancer detection and classification method based on multi-view is rather suitable in clinical practice. Determination of the correspondence between multi-view mammograms is the foundation for multi-view detection. Here, an overview of recent developments in determining correspondence between multi-view mammograms is presented. Nipple detection and pectoral muscle segmentation are first summarized. Both advantages and disadvantages of different methods are compared. Then two-view matching and bilateral matching are discussed. Finally, the problems in the existing matching methods are analyzed and improvements are suggested.