A novel method to look for the hysteresis thresholds for the Canny edge detector

Authors:
R. Medina-Carnicer;R. Muñoz-Salinas;E. Yeguas-Bolivar;L. Diaz-Mas
Affiliations:
Department of Computing and Numerical Analysis, Cordoba University, 14071 Cordoba, Spain;Department of Computing and Numerical Analysis, Cordoba University, 14071 Cordoba, Spain;Department of Computing and Numerical Analysis, Cordoba University, 14071 Cordoba, Spain;Department of Computing and Numerical Analysis, Cordoba University, 14071 Cordoba, Spain
Venue:
Pattern Recognition
Year:
2011

Citing 17
Cited 3

A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Distance transformations in digital images

Computer Vision, Graphics, and Image Processing
Robust Visual Method for Assessing the Relative Performance of Edge-Detection Algorithms

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Objective Edge Detection Evaluation and Detector Parameter Selection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic edge detection using 3 × 3 ideal binary pixel patterns and fuzzy-based edge thresholding

Pattern Recognition Letters
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues

IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-adaptive detection and local characterization of edges based on wavelet transform

Signal Processing - Signal processing in communications
Unimodal thresholding for edge detection

Pattern Recognition
On candidates selection for hysteresis thresholds in edge detection

Pattern Recognition
On mathematical derivations of auto-term functions and signal-to-noise ratios of the Choi--Williams, first- and nth-order hyperbolic kernels

Digital Signal Processing
Solving the process of hysteresis without determining the optimal thresholds

Pattern Recognition
Evaluation of global thresholding techniques in non-contextual edge detection

Pattern Recognition Letters
Determining hysteresis thresholds for edge detection by combining the advantages and disadvantages of thresholding methods

IEEE Transactions on Image Processing
A level set method based on the Bayesian risk for medical image segmentation

Pattern Recognition
A gravitational approach to edge detection based on triangular norms

Pattern Recognition
A geometric approach to edge detection

IEEE Transactions on Fuzzy Systems
Thresholding in edge detection: a statistical approach

IEEE Transactions on Image Processing

Tensor scale: An analytic approach with efficient computation and applications

Computer Vision and Image Understanding
Unsupervised edge detection and noise detection from a single image

Pattern Recognition
A Mathematical Model of Retinal Ganglion Cells and Its Applications in Image Representation

Neural Processing Letters

Quantified Score

Hi-index	0.01

Visualization

Abstract

In the last few years, several works have been proposed to solve the problem of determining the hysteresis thresholds in an unsupervised way. In this paper, a novel method to solve this problem is proposed. Given a set of candidates for hysteresis thresholds, the basic idea of the proposed method is to combine gradient information with information obtained when the linking process is applied to all candidates. Using the same dataset and the same evaluation methodology already proposed by other works, the results obtained by our method show a performance better than that of the previous methods. The results obtained by the proposed method have been validated only for the Canny edge detector, but there are no restrictions on applying the proposed method to any other edge detector whose strategy is based on the hysteresis mechanism.