Research on Spatial Clustering Acetabuliform Model and Algorithm Based on Mathematical Morphology
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
A solution to the deficiencies of image enhancement
Signal Processing
A Clustering Based Method for Edge Detection in Hyperspectral Images
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Line detection in range images
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Image and volume segmentation by water flow
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
A fast and robust image segmentation using FCM with spatial information
Digital Signal Processing
IEEE Transactions on Image Processing
An improved method for edge detection based on interval type-2 fuzzy logic
Expert Systems with Applications: An International Journal
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
Fuzzy morphological polynomial image representation
EURASIP Journal on Advances in Signal Processing - Special issue on time-frequency analysis and its applications to multimedia signals
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
Detecting structure in diffusion tensor MR images
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
AIS'12 Proceedings of the Third international conference on Autonomous and Intelligent Systems
An efficient scheme for color edge detection in uniform color space
AIS'12 Proceedings of the Third international conference on Autonomous and Intelligent Systems
Spectral-spatial classification of hyperspectral imagery based on Random Forests
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
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A new color edge detector based on vector differences is proposed. The basic technique gives as its output the maximum distance between the vectors within a mask. When applied to scalar-valued images, the method reduces to the classic morphological gradient. The technique is relatively computationally efficient and can also be readily applied to other vector-valued images. To improve the performance in the presence of noise, a novel pairwise outlier rejection scheme is employed. A quantitative evaluation using Pratt's figure of merit shows the new technique to outperform other recently proposed color edge detectors. In addition, application to real images demonstrates the approach to be highly effective despite its low complexity.