Image segmentation by the modelisation of the biological visual systems

J. Girod, G. Martin, B. Heit, J. Brémont
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引用次数: 4

Abstract

The segmentation tool presented in this article takes advantage of orientation selection mechanisms which appear in the visual cortex, so that fine, well-situated edges are obtained in a grey-scale image. The search for the best spatial resolution limits our study to the central part of the fovea. The first part of this article deals with a schematic description of the path followed by visual information in the brain and, in particular, from the eye to the primary visual cortex. The model used accepts spatial grouping by the horizontal cells in Gaussian form, and takes advantage of the center-surround antagonism of the bipolar cells found on the retina. The model obtained, which is quite insensitive to noise, reconciles very well the different characteristics of the natural images without setting the parameters. The structure of operations employed in order to carry this out allows a real-time implementation on neural network or pipeline hardware to be envisaged.<>
生物视觉系统建模的图像分割
本文提出的分割工具利用了视觉皮层中出现的方向选择机制,从而在灰度图像中获得精细的、位置良好的边缘。为了寻找最佳的空间分辨率,我们的研究仅限于中央凹的中央部分。本文的第一部分处理视觉信息在大脑中的路径示意图,特别是从眼睛到初级视觉皮层。所使用的模型接受高斯形式的水平细胞的空间分组,并利用在视网膜上发现的双极细胞的中心-周围拮抗作用。该模型对噪声不敏感,在不设置参数的情况下能很好地协调自然图像的不同特征。为了实现这一目标,所采用的操作结构允许在神经网络或管道硬件上实现实时实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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