Unimodal thresholding for edge detection

Authors:
R. Medina-Carnicer;F. J. Madrid-Cuevas
Affiliations:
Department of Computing and Numerical Analysis, Córdoba University, 14071 Córdoba, Spain;Department of Computing and Numerical Analysis, Córdoba University, 14071 Córdoba, Spain
Venue:
Pattern Recognition
Year:
2008

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Abstract

In this paper a novel non-parametric method is proposed for unimodal thresholding in an edge detection context. The proposed method assigns a point in a ROC (receiver operating characteristic) space to each possible threshold without the need of a reference binary image. The optimal point and the required corresponding threshold is then determined in the ROC graph. The Berkeley Segmentation Dataset has been used to evaluate the performance of the proposed method, which is compared with another two recent proposals and Otsu method.