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Edge Detection Techniques For Image Segmentation

ISSN:0975-3826
Journal from gdlhub / 2017-08-14 11:52:34
Oleh : Md. Amjad Hossain1, Pintu Chandra Shill2, Bishnu Sarker1, and Kazuyuki Murase2, International Journal of Computer Science & Information Technology
Dibuat : 2012-07-02, dengan 1 file

Keyword : Computer Vision , Image Segmentation , Edge detection, MATLAB.
Subjek : Edge Detection Techniques For Image Segmentation
Url : http://airccse.org/journal/jcsit/1211csit20.pdf
Sumber pengambilan dokumen : Internet

Interpretation of image contents is one of the objectives in computer vision specifically in image


processing. In this era it has received much awareness of researchers. In image interpretation the


partition of the image into object and background is a severe step. Segmentation separates an image into


its component regions or objects. Image segmentation t needs to segment the object from the background


to read the image properly and identify the content of the image carefully. In this context, edge detection


is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance


of most commonly used edge detection techniques for image segmentation and also the comparison of


these techniques is carried out with an experiment by using MATLAB software.

Deskripsi Alternatif :

Interpretation of image contents is one of the objectives in computer vision specifically in image


processing. In this era it has received much awareness of researchers. In image interpretation the


partition of the image into object and background is a severe step. Segmentation separates an image into


its component regions or objects. Image segmentation t needs to segment the object from the background


to read the image properly and identify the content of the image carefully. In this context, edge detection


is a fundamental tool for image segmentation. In this paper an attempt is made to study the performance


of most commonly used edge detection techniques for image segmentation and also the comparison of


these techniques is carried out with an experiment by using MATLAB software.

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