Image segmentation is the major step for analysis of image. All image segmentation methods depend upon either on intensity values of pixel or on discontinuity and similarity in pixel’s intensity value. In first category, image is segmented based on abrupt change in intensity value. Such abrupt change in intensity value represents an edge in the image. A number of edge detection methods have been developed in area of image processing. Each of which is based on its own method to detect edge points. Edge detection methods are based on discontinuity of image intensity function. Such discontinuity can be detected either using first order derivative or using second order derivative of image intensity function. Different edge detection methods results in identification of different types of edges. Like a few edge detection methods mark edges as thick lines, whereas, some other methods result in detection of edges as thin lines. Some methods use first order derivative of intensity function to detect edges. Whereas, some other methods detect edges using second order derivative of intensity function. From such a large number of edge detection methods, which method one should use depends upon problem being solved and requirement of user.

How to Cite
SUNEJA, Anu; KUMAR, Gaurav. An Experimental Study of Edge Detection Methods in Digital Image. Global Journal of Computer Science and Technology, [S.l.], apr. 2010. ISSN 0975-4172. Available at: <https://computerresearch.org/index.php/computer/article/view/894>. Date accessed: 21 may 2019.