计算机与现代化 ›› 2015, Vol. 0 ›› Issue (8): 13-18.doi: 10.3969/j.issn.1006-2475.2015.08.003

• 图像处理 • 上一篇    下一篇

基于非经典感受野动态调整机制的图像表征计算模型

  

  1. 北京师范大学珠海分校信息技术学院,广东珠海519087
  • 收稿日期:2015-03-18 出版日期:2015-08-08 发布日期:2015-08-19
  • 作者简介:樊一娜(1979-),女,江西南昌人,北京师范大学珠海分校信息技术学院讲师,硕士,研究方向:机器视觉; 郎波(1974-),男,山东潍坊人,副教授,博士,研究方向:计算机视觉,智能媒体技术; 黄静(1967-),女,湖南衡阳人,教授,博士,研究方向:计算机图形学。
  • 基金资助:
    国家自然科学基金资助项目(61272364)

An Image Representation Computation Model Based on Dynamic Adjustment Mechanism of Non-classical Receptive Fields

  1. School of Information Technology, Zhuhai Branch, Beijing Normal University, Zhuhai 519087, China  
  • Received:2015-03-18 Online:2015-08-08 Published:2015-08-19

摘要: 为了寻求一种更好的通用图像表征方式,更好地为提取图像的高层语义服务,利用视网膜神经节细胞非经典感受野的生理机制,设计一种基于神经机制的图像表征网络层次模型,它模拟非经典感受野可以根据图像邻域之间的性质差异进行动态调整的生理机制,从而实现图像在神经层面上的内在表征,以方便进一步提取图像的语义。实验结果表明,与传统的利用单个像素对图像进行表征的方法相比,用神经节细胞非经典感受野来表征图像代价非常小,更重要的是,这种表征方式为图像的语义提取提供了一种基本的框架。

关键词: 视觉系统, 图像表征, 神经节细胞, 非经典感受野

Abstract: This paper utilizes the physiological mechanism of non-classical receptive field of ganglion cell to design a hierarchical network model for image representation based on neurobiology. It is different from the contour detection, edge detection, and other practices using the classical receptive fields, simulating the non-classical receptive fields physiological mechanism which can be dynamically adjusted according to stimulation for image local segmentation and compression based on image neighborhood region similarity, thus realizes the inner image representation in neural representation level and convenients for extract the semantics of image further. We provide extensive experimental evaluation to demonstrate that, comparing with the traditional methods using single pixel, GC-array can represent image with a low cost. Most importantly, the GC-array model provides a basic infrastructure for image semantic extraction.

 

Key words: vision system, image representation, ganglion cell, non-classical receptive field

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