Edge Detection Based on Adaptive Oriented Double Opponent Neurons
文献类型：会议论文
| 作者 | Huiqi Li; Guoru Zhao; ZhenZhang |
| 出版日期 | 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. |
| 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. |
入库方式： OAI收割
来源：深圳先进技术研究院
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