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Edge detection is a very significant feature of image processing and refers to the algorithms, which are intended for identifying points in a digital image where the image intensity changes significantly. The need of edge detection is to find the discontinuities in intensity, surface direction, change in texture properties, and variation in scene illumination. This paper proposes a rapid and superior edge detection technique, which uses the logical operations on circularly shifted images to efficiently detect the edges with lesser computational complexity. The results are compared with other edge detectors using 2-dimensional Fourier transform. Experimental results show that the proposed algorithm improves detection accuracy and possesses encouraging robustness when applied to different images, in comparison to several other edge detection algorithms. Moreover, the algorithm is also applied on a bio-medical application to segment blood cells to show the diversified nature of the proposed algorithm.

Multi-level threshold based edge detector using logical operations