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Assignment of Figural Side to Contours Based on Symmetry, Parallelism, and Convexity

机译:根据对称性,平行性和凸性将图形面分配给轮廓

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摘要

We propose a neural network model for the figure-ground organization based on spatial arrangement of contours such as parallelism, symmetry, and on contour convexity. All of them have been manifested as effective factors for figure-ground organization by psychological studies. In order to measure parallelism and symmetry, spatially separated distant contours have to be corresponded. Our model process them by local detectors embedded in hierarchical architecture of network in which image data is pyramidally encoded. We tested our model by computer simulation and succeeded to mimic some human perceptions.
机译:我们提出了一种基于轮廓的空间排列(例如平行度,对称性和轮廓凸度)的图形地面组织的神经网络模型。所有这些都已被心理学研究证明是影响人物形象组织的有效因素。为了测量平行度和对称性,必须将空间上分开的远处轮廓对应起来。我们的模型通过嵌入网络分层结构中的本地检测器对图像进行处理,在分层结构中图像数据被金字塔式编码。我们通过计算机仿真测试了模型,并成功模仿了一些人类的感知。

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