Learning Towards Image Segmentation Framework Using Region Based Thresholding Techniques

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Dhirendra Pal Singh
Ashish Khare


This paper addresses Image Segmentation Techniques, their performances and efficiency with various gray level images. Image segmentation has been, and still is, a relevant research area in Computer Vision and Image Processing Applications. Computer Vision is a field of artificial intelligence used to program a computer to understand the features in an image; and Image Segmentation, is one of the goal to be achieved using computer vision. In Several Computer Vision Applications like Object Recognition, Robotics and Measurement etc., Image Segmentation techniques are used. If there are a number of targets in an image analysis system, image segmentation is necessary: locating and isolating the targets in an image and then identifying them. Once isolated, the targets can be measured and classified. A variety of image segmentation algorithms have been proposed in last 30 years. Most of the algorithms are specified and good for some particular type of applications, but they are not suited for other applications, hence research and algorithms are in developing stage in this area to provide best results for all kind of applications. In this paper, we enumerate and reviews several popular image segmentation algorithms, specially Regions Based Image Segmentation, discuss their specialties.



Keywords: Image Processing; Image Segmentation; Image Histogram; Threshold.


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