Abstract Background and Objective There are many work related with segmentation
techniques, including nearest neighbor algorithm, fuzzy rules, morphological filters, image
entropy, thresholding, machine learning, wavelet analysis, and so on. Such methods carry
out the segmentation, but take a lot of processing time by modifying the content of the image
or showing discern problems in homogeneous areas, and the segmentation technique is
designed to work efficiently only with the techniques used. In this paper a method to …

In this paper a method to segment mammograms in order to separate breast area from
pectoral muscle and reduce false-positives is presented. The aim of this work is avoid
brightness areas that produce noise. The methodology is divided into four sections: 1)
Preprocessing which consist in acquiring image and decrease its size eliminating the
background. 2) Improve the image quality through image thresholding and histogram
equalization. 3) Localization of regions of interest (ROI) in the image; this is done using …