Region of Interest Prediction using Segmentation 
L. M. Merlin Livingston1, S. Mary Cynthia2
1L.M. Merlin Livingston*, Jeppiaar Institute of Technology, Sriperumbudur, Tamil Nadu, India.
2S. Mary Cynthia, Jeppiaar Institute of Technology, Sriperumbudur, Tamil Nadu, India.
Manuscript received on May 29, 2020. | Revised Manuscript received on June 22, 2020. | Manuscript published on June 30, 2020. | PP: 613-617 | Volume-9 Issue-5, June 2020. | Retrieval Number: D8786049420/2020©BEIESP | DOI: 10.35940/ijeat.D8786.069520
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Segmentation separates an image into different sections badsed on the desire of the user. Segmentation will be carried out in an image, until the region of interest (ROI) of an object is extracted. Segmentation reliability predicts the progress of the various segmentation techniques. In this paper, various segmentation methods are proposed and quality of segmentation is verified by using quality metrics like Mean Squared Error (MSE),Signal to Noise Ratio (SNR), Peak- Signal to Noise Ratio (PSNR), Edge Preservation Index (EPI) and Structural Similarity Index Metric (SSIM).
Keywords: Segmentation, ROI, EPI and SSIM