Journal ArticleDOI
Optimal edge detectors for ramp edges
Maria Petrou,Josef Kittler +1 more
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TLDR
It is argued that the best way to model an edge is by assuming all ideal mathematical function passed through a low-pass filter and and immersed in noise.Abstract:
It is argued that the best way to model an edge is by assuming all ideal mathematical function passed through a low-pass filter and and immersed in noise. Using techniques similar to those developed by J. Canny (1983, 1986) and L.A. Spacek (1986), optimal filters are derived for ramp edges of various slopes. The optimal nonrecursive filter for ideal step edges is then derived as a limiting case of the filters for ramp edges. Because there are no step edges in images, edge detection is improved when the ramp filter is used instead of the filters developed for step edges. For practical purposes, some convolution masks are given which can be used directly for edge detection without the need to go into the details of the subject. >read more
Citations
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Journal ArticleDOI
Edge Detection and Ridge Detection with Automatic Scale Selection
TL;DR: A mechanism is presented for automatic selection of scale levels when detecting one-dimensional image features, such as edges and ridges, with characteristic property that the selected scales on a scale-space ridge instead reflect the width of the ridge.
Proceedings ArticleDOI
Edge detection and ridge detection with automatic scale selection
TL;DR: A mechanism is presented for automatic selection of scale levels when detecting one-dimensional features, such as edges and ridges, and a novel concept of a scale-space edge is introduced.
Book
Feature Extraction and Image Processing
Mark S. Nixon,Alberto S. Aguado +1 more
TL;DR: The new edition of Feature Extraction and Image Processing provides an essential guide to the implementation of image processing and computer vision techniques, explaining techniques and fundamentals in a clear and concise manner, and features a companion website that includes worksheets, links to free software, Matlab files, solutions and new demonstrations.
Edge Detection Techniques-An Overview
Djemel Ziou,Salvatore Tabbone +1 more
TL;DR: An overview of research in edge detection is proposed: edge definition, properties of detectors, the methodology of edge detection, the mutual influence between edges and detectors, and existing edge detectors and their implementation.
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Image Processing: The Fundamentals
TL;DR: This book introduces the mathematical foundations of image processing in the context of specific applications in the four main themes: image enhancement, image compression, image restoration, and preparation of an image for automatic vision.
References
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Journal ArticleDOI
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Journal ArticleDOI
Using Canny's criteria to derive a recursively implemented optimal edge detector
TL;DR: It is shown that a solution to Canny's precise formulation of detection and localization for an infinite extent filter leads to an optimal operator in one dimension, which can be efficiently implemented by two recursive filters moving in opposite directions.
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TL;DR: This thesis is an attempt to formulate a set of edge detection criteria that capture as directly as possible the desirable properties of an edge operator.
Journal ArticleDOI
On Detecting Edges
TL;DR: In this paper, a series of one-dimensional surfaces are fit to each window and the surface description is accepted, which is adequate in the least square sense and has the fewest parameters.
Journal ArticleDOI
Edge detection and motion detection
TL;DR: An integrated theory of edge detection, curvature measurement and motion detection during the earliest stages of visual processing is presented.