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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Application of binocular disparity and receptive field dynamics: A biologically-inspired model for contour detection
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Application of binocular disparity and receptive field dynamics: A biologically-inspired model for contour detection

机译:双目视差和接受场动态的应用:一种生物学激励模型的轮廓检测模型

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摘要

Neurophysiological evidence demonstrates that classical receptive field responses in the primary visual cortex can be modulated by the non-classical receptive field. Although models based on the non-classical receptive field have been proposed, which has not employed the two following characteristics: dynamic regulation of the receptive field under external stimuli and depth determination by binocular cells. We propose a model that includes processing of gray-scale images and depth images. Luminance of grayscale image response was preprocessed using weighted least squares filtering; luminance of grayscale image and disparity information of depth image responses were obtained by V1 neuron responses. The recep-tive field size of each pixel used to calculate the luminance and disparity response is determined by the depth information. Luminance and disparity information responses were combined based on the optimal orientation, and robust contour maps were developed. Experimental results show that the proposed contour detection model outperforms biologically inspired models. (c) 2020 Elsevier Ltd. All rights reserved.
机译:神经生理学证据表明,初级视觉皮层的经典感受野反应可以被非经典感受野调节。虽然已经提出了基于非经典感受野的模型,但该模型没有利用以下两个特点:在外部刺激下感受野的动态调节和双眼细胞的深度确定。我们提出了一个包含灰度图像和深度图像处理的模型。采用加权最小二乘滤波对灰度图像响应亮度进行预处理;通过V1神经元反应获得灰度图像的亮度和深度图像反应的视差信息。用于计算亮度和视差响应的每个像素的接收场大小由深度信息确定。基于最佳方向将亮度和视差信息响应结合起来,并开发出鲁棒的等高线图。实验结果表明,本文提出的轮廓检测模型优于生物启发模型。(c) 2020爱思唯尔有限公司版权所有。

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