Edge Detection Based on Adaptive Oriented Double Opponent Neurons
Huiqi Li; Guoru Zhao; ZhenZhang
2018
会议日期2018
会议地点上海
英文摘要A new method of edge detection based on adaptive oriented double opponent neurons is presented in this paper, considering that the homocentric opponent receptive field is lack of directionality, and the anisotropic of receptive field in ODOG model will be badly restrained during weighting process. To get relatively complete image edges, the edge directional operators are introduced to choose Difference of Gaussians (DOG) model or the orientations of Oriented Difference of Gaussians (ODOG) model automatically. Compared with DOG and ODOG methods, the methods detect weak edges effectively with better edge connectivity and edge confidence.
内容类型会议论文
源URL[http://ir.siat.ac.cn:8080/handle/172644/14497]  
专题深圳先进技术研究院_医工所
推荐引用方式
GB/T 7714
Huiqi Li,Guoru Zhao,ZhenZhang. Edge Detection Based on Adaptive Oriented Double Opponent Neurons[C]. 见:. 上海. 2018.
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