Texture Image Segmentation Based on threshold Techniques

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Published: Mar 28, 2017
Keywords:
Segmentation, Edge Detection, Region Based, threshold-based segmentation techniques.

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Dodla. Likhith Reddy
Dept.of ECE, PBR VITS, KAVALI.
Dr. D Prathyusha Reddi
Dept.of ECE, PBR VITS, KAVALI.

Abstract

Image segmentation is the process of partitioning a digital image into multiple segments. The goal of segmentation is to simplify and change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is used to extract the values of objects and boundaries in a selected image, such as lines and curves. The process of image segmentation plays a critical role in various pattern recognition applications, including robot vision, cartography, criminal investigation, remote sensing, object identification and recognition, military surveillance, quality assurance in industries, facial recognition, and medical imaging, among others. The main aim of this paper is to propose methods for improving image segmentation and providing a clear understanding of the objects within the image using different techniques. This article presents a brief outline of some of the most commonly used segmentation techniques, including Thresholding, Region-based, and Edge detection methods. The proposed methods are implemented in MATLAB.

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How to Cite
[1]
Dodla. Likhith Reddy and Dr. D Prathyusha Reddi, “Texture Image Segmentation Based on threshold Techniques”, Int. J. Comput. Eng. Res. Trends, vol. 4, no. 3, pp. 69–75, Mar. 2017.
Issue
Vol. 4 No. 3 (2017): March (2017) Issue
Section
Research Articles
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