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Edge Detection using Third Order Difference Equation: A New Dimension

G. J. Joyce Mary, A. Rijuvana Begum Published in Image Processing

Communications on Applied Electronics
Year of Publication: 2015
© 2015 by CAE Journal

G.j.joyce Mary and A.rijuvana Begum. Article: Edge Detection using Third Order Difference Equation: A New Dimension. Communications on Applied Electronics 1(6):10-14, April 2015. Published by Foundation of Computer Science, New York, USA. BibTeX

	author = {G.j.joyce Mary and A.rijuvana Begum},
	title = {Article: Edge Detection using Third Order Difference Equation: A New Dimension},
	journal = {Communications on Applied Electronics},
	year = {2015},
	volume = {1},
	number = {6},
	pages = {10-14},
	month = {April},
	note = {Published by Foundation of Computer Science, New York, USA}


Edges are the regions of object where there is a pointed change in intensity or gray level. Edge detection is one of the most frequently used operations in image analysis. If the edges are accurate, all the objects are located efficiently and the performance can be evaluated easily. Process of Edge detection is really a complicated task. Lot of research has been done in this field for many years. Object recognition, Target tracking, Segmentation, Data compression and Image matching are the most important areas of application where edge detection is highly required. This paper introduces a new edge detection technique using derivative mask. This mask is based on third order difference equation. The experimental results demonstrate the effectiveness of the new edge detector in terms of PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error). Performance of this new mask compared with second order Laplacian Mask. Proposed mask is efficient and faster to implement. Experimental result on various images shows all the edges efficiently.


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Edge, Third Order, Difference equation, Mask, PSNR, MSE