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A Guide Tour on the Techniques of Image Segmentation


Affiliations
1 Department of Electronics and Communication Engineering, Mewar University, Chittorgarh, India
2 Department of Electronics and Communication Engineering, North Cap University, Gurgaon, Haryana, India
     

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The image segmentation is one of the most important emerging part in the field of image processing that divides an image in segments for easy analysis of image. Several image segmentation techniques have been developed by the researchers for fine recognition of every segment of image for further processing like recognition ,compression. The level to which the subdivision is carried depends on the problem being solved. That is, segmentation should stop when the objects of interest in an application have been isolated .This paper presents a brief outline on some of the most commonly used segmentation techniques like threshold , Region based, Model based, Edge detection.

Keywords

Threshold, Region Based, Model Based, Edge Based, Clustering Based.
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  • A Guide Tour on the Techniques of Image Segmentation

Abstract Views: 310  |  PDF Views: 3

Authors

Shaloo Kikan
Department of Electronics and Communication Engineering, Mewar University, Chittorgarh, India
Ashima Arora
Department of Electronics and Communication Engineering, North Cap University, Gurgaon, Haryana, India

Abstract


The image segmentation is one of the most important emerging part in the field of image processing that divides an image in segments for easy analysis of image. Several image segmentation techniques have been developed by the researchers for fine recognition of every segment of image for further processing like recognition ,compression. The level to which the subdivision is carried depends on the problem being solved. That is, segmentation should stop when the objects of interest in an application have been isolated .This paper presents a brief outline on some of the most commonly used segmentation techniques like threshold , Region based, Model based, Edge detection.

Keywords


Threshold, Region Based, Model Based, Edge Based, Clustering Based.