An Operator Which Locates Edges in Digitized Pictures
Journal of the ACM (JACM)
A Local Visual Operator Which Recognizes Edges and Lines
Journal of the ACM (JACM)
Optimal Piecewise Polynomial L2Approximation of Functions of One and Two Variables
IEEE Transactions on Computers
Detection of Step Edges in Noisy One-Dimensional Data
IEEE Transactions on Computers
Deducing local influence neighbourhoods with application to edge-preserving image denoising
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
The fuzzy geometry of image subsets
Pattern Recognition Letters
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Suppose that we are given a picture having approximately piecewise constant gray leveL Each point P has a largest neighborhood N(P) that is entirely contained in one of the constant regions, and the set of maximal N(P)'s (i.e., N(P)'s not contained in other N(P)'s) constitutes an economical description of the picture, generalizing the Blum "skeleton" or medial axis transformation. This description can be used to construct approximations to the picture (e.g., by discarding small N(P)'s). The picture can be smoothed, without excessive blurring, by averaging over each N(P). By taking differences between pairs of touching maximal N(P)'s, the edges between the regions can be detected; since this edge detection scheme is not based on symmetrical detection operators, it is not handicapped when two adjacent regions differ greatly in size.