Detection of Calcification form Mammogram Image using Canny Edge Detector

Objectives: To help the physician to identify the amount of calcium in the breast cells as part of cancer detection. Methods/ Statistical Analysis: In this paper we compare the analysis of two different algorithms: Watershed method of identifying the cancer cells and edge detection by canny edge detection. The comparison was taken for the same mammogram image sequence. Initially, preprocessing like filtering and resizing was done for the mammogram images. Preprocessed images were appended to the cancer affected location by edge detection by canny edge detector. It used for identifying the depth of the calcification in a mammogram image sequence. This is turn into the appropriate examination. Findings: The watershed algorithm produces the entire calcium affected areas with major super imposed color. Whereas, in canny edge detector the minor cells were highly identified by the calcium affected cells. This would help physician for appropriate treatments. Application/ Improvements: This is the best algorithm for the distribution of calcification over a distance.