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分形边界的视觉辨别

Visual discrimination of fractal borders.

作者信息

Westheimer G

机构信息

Department of Molecular and Cell Biology, University of California, Berkeley 94720.

出版信息

Proc Biol Sci. 1991 Mar 22;243(1308):215-9. doi: 10.1098/rspb.1991.0034.

Abstract

The ideas of fractals and fractal dimension are here translated into the realm of visual psychophysics. Borders between two fields of different luminance were used. Because of the finite grain of the visual system, fractal dimension need be defined only within a certain size range. For a fractal dimension of 1.15, the just-detectable difference in fractal dimension was found to be about 0.0085, rising to about 0.015 for a fractal dimension of 1.25. Reducing exposure duration from 1 s to 0.33 s decreases sensitivity to differences in fractal dimension, but there was no gain in increasing the exposure duration. Good visual observers who are naive to the task require some training before reaching optimal performance. The ability to discriminate fractal dimension differs between fractal edges of the same fractal dimension that were generated with differing statistical programs. Even after considerable training, an observer makes 29% errors when asked to distinguish a fractal edge generated with a Gaussian random walk from one with a rectangular random walk. Gaussian random walk fractals can be more easily distinguished from Poissonian and Cauchy ones.

摘要

分形和分形维数的概念在此被引入视觉心理物理学领域。使用了不同亮度的两个区域之间的边界。由于视觉系统的有限粒度,分形维数只需在一定尺寸范围内定义。对于分形维数为1.15的情况,发现分形维数的刚可察觉差异约为0.0085,对于分形维数为1.25的情况则升至约0.015。将曝光持续时间从1秒减少到0.33秒会降低对分形维数差异的敏感度,但增加曝光持续时间并无增益。对该任务不熟悉的优秀视觉观察者在达到最佳表现之前需要一些训练。区分分形维数的能力在使用不同统计程序生成的相同分形维数的分形边缘之间存在差异。即使经过大量训练,当观察者被要求区分由高斯随机游走生成的分形边缘和由矩形随机游走生成的分形边缘时,仍会出现29%的错误。高斯随机游走分形比泊松和柯西分形更容易区分。

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