基于长短时程突触互补网络的边缘检测方法

doi:10.3969/j.issn.0258-8021.2020.06.001

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Abstract The accuracy of edge detection is of great significance for improving the performance of artificial visual perception systems. In this work, a neural network with long and short-term synaptic complementarity was constructed. First, the dominant color antagonistic characteristics of cone cells were introduced, and the color antagonistic channels of the image to be tested were weighted to obtain the primary edge perception of the image to be tested. the synchronous firing characteristics of the neuron group were simulated, the synapse dynamically connected neuron action window was defined, and the group discharge time coding of the primary edge perception was realized; then a long- and short-term synaptic complementary module was built based on the synchronous firing of the neuron group in the short-term characteristics and the temporal and spatial dependence of neuron firing activity in the long-term, to achieve long- and short-term synaptic plasticity coding and complementary fusion. At last, the edge response by encoding the temporal information stream was obtained. The 20 pairs of colony images collected by the laboratory according to the needs of routine microbiological experiments were used as experimental materials, and the reconstructed similarity MSSIM, edge confidence BIdx, and comprehensive index EIdx were used as evaluation indicators. Results showed that, compared with the three mainstream methods of VSC, NIS and MSP, the detection results of the algorithm of this study had accurate edges and a low missed detection rate, which was consistent with the results of artificial subjective observations; meanwhile, the mean and standard deviation of the three indicators of MSSIM, BIdx and EIdx was 0.909 6±0.037 7, 0.671 5±0.105 7, and 0.804 8±0.052 1 respectively, and the overall performance was better than the above three mainstream methods. The method provided a new idea for realizing the construction of visual perception computing model and its application in image processing by simulating the long- and short-term synaptic complementarity of the neuron population.

Key words： edge detection dominant color antagonism synaptic dynamic connection synaptic plasticity long- and short-term synaptic complementarity

Received: 28 February 2020

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	Articles by authors
	Yu Xiang
	Fan Yingle
	Fang Tao
	Wu Wei

Cite this article:

Yu Xiang,Fan Yingle,Fang Tao, et al. Edge Detection Method Based on the Long- and Short-Term Synaptic Complementary Networks[J]. Chinese Journal of Biomedical Engineering, 2020, 39(6): 641-651.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2020.06.001 OR http://cjbme.csbme.org/EN/Y2020/V39/I6/641

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