Title :
Edge detection by regularized cubic B-spline fitting
Author_Institution :
Comput. Vision Lab., Saskatchewan Univ., Saskatoon, Sask.
fDate :
4/1/1995 12:00:00 AM
Abstract :
In this paper, regularized cubic B-spline fitting (RCBS), a technique which combines conventional cubic B-splines with regularization techniques, is proposed for the detection of edges. In addition, a quantitative performance evaluation model, called the false-detected to correct-detected ratio (FCR) model, is proposed for the evaluation of edge detectors. The FCR model attempts to provide a common ground for the quantitative performance evaluation and comparison between different edge detection schemes. The experimental results using the FCR model show that the RCBS operator is superior with respect to noise immunity and localization in comparison with two commonly used operators: the Sobel operator and Haralick´s bivariate cubic polynomial operator
Keywords :
curve fitting; edge detection; performance evaluation; splines (mathematics); edge detection; evaluation model; false-detected to correct-detected ratio model; localization; noise immunity; regularization techniques; regularized cubic B-spline fitting; Computer vision; Detectors; Filtering; Image edge detection; Image processing; Matched filters; Polynomials; Spline; Surface fitting; Working environment noise;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on