Proposed algorithm for using GLCM properties to distinguishing geometric shapes

• Published in: AL-Rafidain journal of computer sciences and mathematics Vol. 13; no. 1; pp. 32 - 47
• Main Author: Thanun, Kifaa Hadi
• Format: Journal Article
• Language: English
• Published: Mosul, Iraq University of Mosul, College of Computer Science and Mathematics 05.06.2019; Mosul University
• Subjects: co-occurrence matrix; feature extraction; shapes; texture analysis; الخوارزميات; الهندسة
• ISSN: 1815-4816; 2311-7990; 2311-7990
• DOI: 10.33899/csmj.2020.163501

In this research, an algorithm was used to look at the characteristics of a set of images for geometric shapes and then to classify them into totals based on four characteristics obtained from the co-occurrence matrix (energy, contrast, correlation and homogeneity). Studying the above four characteristics in detail and then presenting a complete presentation on the extent of their effect on the distinctive characteristics of the geometrical shapes. The adopted algorithm shows that the above four qualities can be new features of geometric shapes in digital images. The results of the practical application of the proposed algorithm show that the three features of homogeneity, energy, and contrast give a topical distinction to the shape, but the correlation property is weak in the distinction of shape. The algorithm was programmed using MATLAB R2010a for Windows 7 operating system on the computer that has the following specifications: (Processor Intel (R) Core (TM) i5, CPU 640 M & 2.53 GHZ, RAM 6GB)