Using Symmetrical Threshold Contour Algorithm for Skin Cancer Image Segmentation

Lakshmi, B. Vasantha and Sridevi, K. and Sailaja, V. and Sunitha, P. and Kumar, G. S. Siva and Viranya, G. (2024) Using Symmetrical Threshold Contour Algorithm for Skin Cancer Image Segmentation. In: Research Updates in Mathematics and Computer Science Vol. 2. B P International, pp. 134-149. ISBN 978-81-971889-7-8

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Abstract

This study primarily focuses on skin cancer image segmentation based on symmetrical threshold contour algorithm Image segmentation is classification or identification of small patterns in the given images. Image segmentation is a fundamental step in image processing. Image segmentation is the classification of an image into various groups. Research has been done in image segmentation using image clustering methods like k-means clustering algorithm. The approach describes the skin cancer image segmentation based on symmetrical threshold contour algorithm with similar thresholding values for segmentation of the accurate cancerous lesion. Skin cancer lesion shape and structure is the most important parameter in this method. In this paper, skin cancer image contour detection is based on symmetrical thresholding algorithm using MATLAB soft ware. Results of the proposed method are compared with dilation of image morphological algorithm and its contour. By observing the dilated image and its contour, the proposed method gives continuous and accurate contour.

Item Type: Book Section
Subjects: Pustakas > Mathematical Science
Depositing User: Unnamed user with email support@pustakas.com
Date Deposited: 03 Apr 2024 09:34
Last Modified: 03 Apr 2024 09:34
URI: http://archive.pcbmb.org/id/eprint/1931

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