All applications which is based on used to isolate an object from the background is very important image when the conditions are poor and non-uniform way. In case of illumination it needs to adopt the various techniques, which extract the impurity from the image and give the result as a background on any data. To analyses the medical image efficiently and accurately, Image segmentation is one of the ways. Segmentation deals with objects by extracting from the image background. Now days, image segmentation is used in various research fields and numerous approaches in terms of intensity, color, texture etc. The principle point of this paper to review and survey differentiate effective strategies of image segmentation. While comparing all segmentation techniques used in machine learning and deep learning, most of them identifies that deep learning gives best results in terms of effectiveness and exactness of results which can be used in various fields where image processing is being used.
Volume 11 | 11-Special Issue
Pages: 1252-1256
DOI: 10.5373/JARDCS/V11SP11/20193376