Title :
Using local structure for the reliable removal of noise from the output of the LoG edge detector
Author :
Masoud, Ahmad A. ; Bayoumi, Mohamed M.
Author_Institution :
Dept. of Electr. Eng., Queen´´s Univ., Kingston, Ont., Canada
fDate :
2/1/1995 12:00:00 AM
Abstract :
This paper tackles an important problem in image processing; that is, the detection of edges in natural scenes. A scheme that combines simplicity with the ability to detect intensity jumps at widely varying contrasts is proposed. The scheme is constructed by combining the Laplacian-of-Gaussian (LoG) edge detector with a noise removal mechanism. The mechanism is built around a proposed definition for potentially valid edge contours that incorporates their local structure in the filtering process. Some of the advantages of the proposed approach include accurate localization of the edges and ease of implementation. Simulation results as well as statistical analysis of the approach for the 1-D case are provided
Keywords :
Laplace transforms; edge detection; noise; statistical analysis; Laplacian-of-Gaussian edge detector; edge contours; filtering process; image processing; intensity jumps; local structure; natural scenes; reliable noise removal; statistical analysis; Analytical models; Detectors; Filtering; Gaussian noise; Image edge detection; Image processing; Layout; Machine vision; Navigation; Statistical analysis;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on