A Robust Method for Extracting Texture Features of Segmented Mammogram Images using M-ROI Technique
R Suresh1, B. Vjaya2
1Dr. R. Suresh, Professor, Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Tirupati (A.P), India.
2Vijaya, Assistant Professor, Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Tirupati (A.P), India.
Manuscript received on 16 May 2019 | Revised Manuscript received on 12 April 2023 | Manuscript Accepted on 15 May 2023 | Manuscript published on 30 May 2023 | PP: 49-53 | Volume-12 Issue-1, May 2023 | Retrieval Number: 100.1/ijrte.A1821058119 | DOI: 10.35940/ijrte.A1821.0512123
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Abstract: Radiologists generally uses mammogram images for extracting masses or cancer effected breast issues using texture features of the images by segmenting techniques. The most commonly used technique in this process is region of interest (ROI). But this method fails for large collection of mammogram image database. To address this issue this present paper proposed multi-ROI (M-ROI) technique. This method not only reduces limitations of ROI but also finds the very suitable texture features. This paper also evaluated the efficiency of the proposed M-ROI method using first order and second order statistical techniques.
Keywords: Benchmarked Images, Multi-ROI Segmentation, Region of Interest, Texture Features
Scope of the Article: Routing, Switching and Addressing Techniques