A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonparametric tests for edge detection in noise
Pattern Recognition
A regularized solution to edge detection
Journal of Complexity
Adaptive Determination of Filter Scales for Edge Detection
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Scale-Space Theory in Computer Vision
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Elements of Early Vision for Computer Graphics
IEEE Computer Graphics and Applications
Statistical Edge Detection: Learning and Evaluating Edge Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution sequential edge linking
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
A Classified and Comparative Study of Edge Detection Algorithms
ITCC '02 Proceedings of the International Conference on Information Technology: Coding and Computing
A Fast Multiscale Edge Detection Algorithm Based on a New Edge Preserving PDE Resolution Scheme
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Digital Image Processing (3rd Edition)
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Particle swarm optimization for integer programming
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
A high performance edge detector based on fuzzy inference rules
Information Sciences: an International Journal
Edge detection improvement by ant colony optimization
Pattern Recognition Letters
Expert Systems with Applications: An International Journal
A discrete particle swarm optimization algorithm for scheduling parallel machines
Computers and Industrial Engineering
Fractional differentiation and non-Pareto multiobjective optimization for image thresholding
Engineering Applications of Artificial Intelligence
Expert Systems with Applications: An International Journal
On candidates selection for hysteresis thresholds in edge detection
Pattern Recognition
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Robust edge detection in noisy images
Computational Statistics & Data Analysis
A survey of particle swarm optimization applications in electric power systems
IEEE Transactions on Evolutionary Computation
Efficient edge detection using simplified Gabor wavelets
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
Gradient histogram: Thresholding in a region of interest for edge detection
Image and Vision Computing
Handling constraints in particle swarm optimization using a small population size
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Expert Systems with Applications: An International Journal
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Swarm algorithms with chaotic jumps applied to noisy optimization problems
Information Sciences: an International Journal
An Optimal Frequency Domain Filter for Edge Detection in Digital Pictures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gaussian-based edge-detection methods-a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An elastic contour matching model for tropical cyclone patternrecognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A novel image interpolation method using the bilateral filter
IEEE Transactions on Consumer Electronics
Adaptive snakes using the EM algorithm
IEEE Transactions on Image Processing
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Detection of continuous edges is a hard problem and most edge detection algorithms produce jagged and thick edges particularly in noisy images. This paper firstly presents a novel constrained optimisation model for detecting continuous, thin and smooth edges in such images. Then two particle swarm optimisation-based algorithms are applied to search for good solutions. These two algorithms utilise two different constraint handling methods: penalising and preservation. The algorithms are examined and compared with a modified version of the Canny algorithm as a Gaussian filter-based edge detector and the robust rank order (RRO)-based algorithm as a statistical-based edge detector on two sets of images with different types and levels of noise. Pratt's figure of merit as a measure of localisation accuracy is used for the comparison of these algorithms. Experimental results show that the proposed edge detectors are more robust under noisy conditions and their performances are better than the Canny and RRO algorithms for the images corrupted by impulsive and Gaussian noise. The proposed algorithm based on the penalising method is faster than the algorithm using the preservation method to handle the constraints.