Binarizing The Images Using Opencv For Analyzing Image Significance

Abstract

Medical image processing is most important and challenging field now a days. Image preprocessing of brain MRI and its analysis is act of examining images for identifying objects and analyzing their significance. In medical image processing early detection and analysis of brain cancer is most difficult and time consuming task. In medical field image processing techniques are used for improving early detection and treatment stages, especially in various cancers. Image segmentations refer to process of partitioning the image into multiple segments for locating objects and boundaries in image. Image thresholding is one of the techniques for image segmentation to binarize the image based on pixel intensities as it partitions the image into two groups of pixels.  In this proposed work three methods of image thresholding has been implemented. Three techniques are simple thresholding, adaptive thresholding and Otsu’s thresholding are applied specifically on brain cancer MRI image. The implementation work is done by using python open CV library. To check the performance of each image thresholding technique, black pixel and white pixel ratio has been calculated.