• A. Rama Krishna Prasad
• D. Vandana
• N. Lakshmi
• SK.Arshiya
• K. Teja Sri

Image segmentation is one of the most important processes involved in image processing. Segmenting an image is breaking it up into smaller pieces, or segments. These are the areas where it is most helpful because processing the complete image would be inefficient for tasks like object recognition or image compression. Image segmentation is the process of dividing an image's elements for further processing. This article looked at a number of image segmentation techniques, including the threshold approach, edge-based method, and clustering-based method. The segmentation method that is most effective for separating images in OCT images is clustering-based segmentation. To reduce the speckle noise during preprocessing, the wiener filter approach is used. With regards to the threshold, edge-based (Sobel, Canny, Robert's), and clustering-based segmentation techniques, calculate MSE (mean square error) and PSNR (peak signal to noise ratio) values for the segmented image quality.

IMAGE SEGMENTATION TECHNIQUES

"ANALYSIS OF VARIOUS IMAGE SEGMENTATION TECHNIQUES ON RETINAL OCT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.b349-b355, May-2025, Available :http://www.jetir.org/papers/JETIR2505141.pdf

"ANALYSIS OF VARIOUS IMAGE SEGMENTATION TECHNIQUES ON RETINAL OCT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppb349-b355, May-2025, Available at : http://www.jetir.org/papers/JETIR2505141.pdf