An Image Representation Method Based on Retina Mechanism for the Promotion of SIFT and Segmentation

被引：0

作者：

Wei, Hui ^{[1
]}

Lang, Bo ^{[1
]}

Zuo, Qing-Song ^{[1
]}

机构：

[1] Fudan Univ, Dept Comp Sci & Technol, Shanghai 200433, Peoples R China

来源：

NEURAL INFORMATION PROCESSING, ICONIP 2012, PT V | 2012年 / 7667卷

关键词：

image representation; non-classical receptive field; ganglion cell; SIFT; segmentation; RECEPTIVE-FIELD;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a bio-inspired neural network was constructed. It could represent images effectively and provide a processing method for image understanding. Our model adopted the retinal ganglion cells (GCs) and their non-classical receptive field (nCRF) can dynamic self-adjusts according to the characteristics of the image. Extensive experimental evaluations to demonstrate that this kind of representation method was able to make for SIFT detector for focus on foreground object more correctly, and promote the result of image segmentation significantly.

引用

页码：378 / 385

页数：8

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