A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Edge Detection in Noisy Images Using the Support Vector Machines
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
A new efficient SVM-based edge detection method
Pattern Recognition Letters
Scale-adaptive detection and local characterization of edges based on wavelet transform
Signal Processing - Signal processing in communications
Edge detection using ant algorithms
Soft Computing - A Fusion of Foundations, Methodologies and Applications
A novel approach for edge detection based on the theory of universal gravity
Pattern Recognition
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
Improved Canny Edges Using Ant Colony Optimization
CGIV '08 Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation
On candidates selection for hysteresis thresholds in edge detection
Pattern Recognition
GSA: A Gravitational Search Algorithm
Information Sciences: an International Journal
A shearlet approach to edge analysis and detection
IEEE Transactions on Image Processing
An Improved CANNY Edge Detection Algorithm
IWCSE '09 Proceedings of the 2009 Second International Workshop on Computer Science and Engineering - Volume 01
Novel Edge Detection Using BP Neural Network Based on Threshold Binarization
ICCEE '09 Proceedings of the 2009 Second International Conference on Computer and Electrical Engineering - Volume 02
IEEE Transactions on Image Processing
A gravitational approach to edge detection based on triangular norms
Pattern Recognition
BGSA: binary gravitational search algorithm
Natural Computing: an international journal
An efficient ant-based edge detector
Transactions on computational collective intelligence I
A novel bacterial foraging technique for edge detection
Pattern Recognition Letters
An edge detection method by combining fuzzy logic and neural network
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Edge detection of laser range image based on a fast adaptive ant colony algorithm
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Gaussian-based edge-detection methods-a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An adaptive neuro-fuzzy system for automatic image segmentation and edge detection
IEEE Transactions on Fuzzy Systems
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In this paper, a new algorithm for image edge detection based on the theory of universal gravity is proposed. The problem is represented by a discrete space in which each image pixel is considered as a celestial body and its mass is considered to be corresponding to the pixel's grayscale intensity. To find the edgy pixels a number of moving agents are randomly generated and initialized through the image space. Artificial agents move through the space via the forces of celestial bodies that are located in their neighborhood and in this way they can find the promising edge pixels. A large number of experiments are employed to determine suitable algorithm parameters and confirm the legitimacy of the proposed algorithm. Also, the results are compared with conventional and soft computing based methods like Sobel, Canny and ant-based edge detector. As compared to other standard techniques, our algorithm provides more accurate results over 11 test images via Baddeley's error metric. The visual and quantitative comparisons reveal the effectiveness and robustness of the proposed algorithm.