|International Computer Science and Engineering Society (ICSES)|
ICSES Transactions on Image Processing and Pattern Recognition
Vol. 4, No. 4, Dec. 2018
A Survey and Comparative Analysis on Image Segmentation Techniques | Book Chapter of Image Segmentation: A Guide to Image Mining
Vikramsingh Parihar a,, Hamid Reza Boveiri b
Highlights and Novelties
Image segmentation is the very first step in almost all the image processing applications where the properties of objects in images are need to be analyzed. By objects, we mean information of the image like color, texture, shape, edges, boundaries and structure. Various different algorithms have been employed to extract this information from the images. This paper provides a systematic review of image segmentation approaches. Our survey focuses on five key aspects: concept used by the authors, the performance evaluation parameter used by them, the database used, claims by those authors and our findings. Also, the whole analysis is presented by categorizing the different segmentation approaches in five parts; graph based methods, thresholding based methods, clustering methods, edge based approached and contours/wavelet based methods. The whole idea of the work is to provide a systematic and comparative analysis of the various approaches. Also, relevant databases and the list of performance parameters is also provided.
© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors.
Cite this manuscript as
Vikramsingh Parihar, Hamid Reza Boveiri, "A Survey and Comparative Analysis on Image Segmentation Techniques," in Image Segmentation: A Guide to Image Mining, 1st ed., ITIPPR: ICSES, 2018, pp. 1-15.
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