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An Image Thresholding Method Based on Human Visual Perception

机译:一种基于人类视觉感知的图像阈值方法

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摘要

A novel thresholding method based on human visual perception is presented in this paper. The method first utilizes statistical characteristics of an image to choose two gray levels as candidate thresholds by the properties of human visual perception, and then determines the one having minimum standard deviation sum as the optimal threshold. Choice of candidate thresholds reduces search space of thresholds and accelerates threshold selection. The proposed method was compared with several classic thresholding methods on a variety of nondestructive testing (NDT) images and general real world images, and experimental results show its effectiveness and efficiency.
机译:本文介绍了一种基于人类视觉感知的新型阈值化方法。该方法首先利用图像的统计特征来选择两个灰度级,作为人类视觉感知的属性作为候选阈值,然后确定具有最小标准偏差和作为最佳阈值的阈值。选择候选阈值可减少阈值的搜索空间并加速阈值选择。将所提出的方法与多种无损检测(NDT)图像和一般现实世界图像进行多种经典阈值方法,实验结果表明其有效性和效率。

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