Date of Publication :8th August 2024

Abstract: Image extraction or countering is the process of identifying structural outlines of objects in image that can help to detect the object shape. Image segmentation is process that plays important role to interpret a picture very well. Segmentation process is simplifying the image as a group of segments that collectively covers the complete image or a group of contours extracted from the image. It also separates the image into multiple segments (set of pixels) and each segment possesses different features like texture, color, intensity and many statistical properties. For any image to be processed, segmentation is a prime task to visualize the ROI (Region of Interest). Accurate segmentation is required in crucial areas as medical image retrieval where it may contribute to save and protect human life. This paper focusses on implementation of algorithms for identifying brain tumor in MR images, furthermore it involves applying noise removal techniques followed by enhancing the images using image segmentation. This paper is focused on applying segmentation techniques for finding suspicious region in Brain Cancer Magnetic Reasoning Image (MRI). Further the contours are highlighted from the brain cancer MRI using edge-based segmentation. To do this, first detection of the edges of features is performed using Canny edge-detector further region-based method is applied using watershed transform. Finally, the comparative analysis is depicted between various segmentation technique regarding the contour detection.

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