Abstract:

Since edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of edge detection algorithms. This paper evaluates the performance of Prewitt Edge Detector for detection of edges in digital images corrupted with different kinds of noise. Different kinds of noise are studied in order to evaluate the performance of the Prewitt Edge Detector. Further, the various standard test Images are examined to validate our results. The software is developed using MATLAB 7.0.1 It has been observed that the Prewitt Edge Detector works effectively for the digital images corrupted with Poisson Noise where as its performances reduces sharply for other kinds of noise in digital images. The results of this study are quite promising.

Keywords: Edge Detector, Digital Image Processing,Noise

Author Biography:

Raman Maini, received B.Tech(Computer Science & Engineering) from Beant College of Engineering, Gurdaspur, Punjab, India in 1999 and M.Tech( Computer Science & Engineering) from PAU, Ludhiana, India , in 2002. He got Merit certificate in his M.Tech thesis at PAU He is currently working as an Assistant Professor in Computer Engineering at University College of Engineering, Punjabi University, Patiala, India. He is a life member of ISTE (Indian Society of Technical Education), India, IETE (Institution of Electronics & Telecommunication Engineers), India. His current area of research is Computer Vision (Specialty Noise Reduction in Medical Images, Edge Detection and Image Enhancement)

J.S.Sohal, received M.Tech(Electronics &Communication Engineering) from Indian Institute of Technology, Roorkee Uttar Pradesh, India in 1973. He received his Ph.D(Electronics & Communication Engineering) in 1976 from Indian Institute of Technology, Roorkee, Uttar Pradesh, India

BibTex:

@ARTICLE{P1150636001,

AUTHOR = {Raman Maini and J.S.Sohal },

TITLE = {Performance Evaluation of Prewitt Edge Detector for Noisy Images},

JOURNAL ={ICGST International Journal on Graphics, Vision and Image Processing},

}

(Full Paper 590KB)