• Rishm
• Dr. Naresh Kumar Garg

Partitioning of a digital image into different segments is called image segmentation. The main goal of segmentation is to simplify the complex image so that it can easily help us in locating objects and their boundaries like line, curves etc. In segmentation we provide label to every pixel in the image in such a way the pixels with the same label have same characteristics. They are computed on the basis of local or global features whereas local features are categorized by edges, corners, lines, region and global features include texture, shape and colour. Segmenting the liver is difficult task but it can be made little easy using feature extraction. Chan-Vese model (CV model) is successfully applied for the segmentation of liver which is derived from Mumford-Shah functional that is used for segmentation to get shape prior information of liver and to retrieve statistical image intensity information. The results obtained with the proposed technique are very challenging.

CV Model, Segmentation, Features, Shape Prior

"Liver Segmentation Based On Feature Extraction and Shape Prior Features Using CV Model ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.101-104, July-2018, Available :http://www.jetir.org/papers/JETIR1807365.pdf

"Liver Segmentation Based On Feature Extraction and Shape Prior Features Using CV Model ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp101-104, July-2018, Available at : http://www.jetir.org/papers/JETIR1807365.pdf