IMAGE EDGE DETECTION BASED ON ADAPTIVE FUZZY MORPHOLOGICAL NEURAL NETWORK
The fuzzy hit-or-miss transformation is a fuzzy morphological operator, which is a key for the feature extraction in the ambiguous information. In this paper, a neural network implementation for fuzzy morphological operators is proposed, and by means of a training method and differentiable equivalent representations for the operators, efficient adaptive algorithms to optimize structuring elements are derived. The gradient of the fuzzy morphology utilizes a set of structuring elements to detect the edge strength with a view to decrease the spurious edge and suppressed the noise. Results will be presented for images in comparison with the others edging detectors.
Adaptive fuzzy morphological neural network Morphological operation Edge detectors Image processing
GUO-QING YANG YAN-YING GUO LI-HUI JIANG
General Administration of Civil Aviation of China, PeKing 100710, China Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China, Tianjin,300300, C
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
3725-3728
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）