Segmentation Techniques for Mammogram-A Comparative Study

Image segmentation techniques are is reliably used as a piece of medical image abruptly. Breast cancer has been rising tenaciously and lethal killer infirmity of the new time. Medical images have made an extraordinary effect on medicine, diagnosis and treatment. Mammography plays an essential affectation in the detection of breast cancer. Thresholding is a vital strategy for image segmentation. Among all segmentation method, Otsu method is one of the most standout methods for image thresholding. Clustering is one of the methods used for segmentation. Clustering approach is typically used in biomedical image segmentation and it is application are used for breast cancer detection to find out the tumor on the breast. The k-means is one of the pristine clustering algorithms which is perpetually used in several applications. The objective of this paper is to compare watershed, otsu and k-means segmentation using the metrics and find out which technique is best for the detection of breast cancer.