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Differences in recognition of fragmented noisy and non-noisy images revealed by modeling

机译:建模揭示的碎片化噪声和非噪声图像识别差异

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Experimental data on the recognition of fragmented contour images with and without noise are compared with the results of recognition process modeling. A reliable approximation in the matched filtering model for erroneous responses in both stimulation cases was obtained only when the contours were replaced with the image silhouettes. The number of correct responses depended on the contour lengths for the case of images without noise and on the number of extended oriented contour sections for the case of noisy images. This indicates the significant role of the extraction of orientations related to the law of good continuation known from Gestalt psychology in the recognition of noisy images. Therefore, differences between noisy fragmented images and fragmented images without noise were determined in the modeling of the recognition process; i.e., the recognition dependence on the background or target environment was demonstrated. (C) 2021 Optical Society of America
机译:将有噪点和无噪点的碎片轮廓图像识别实验数据与识别过程建模结果进行了比较。只有在将轮廓替换为图像轮廓时,才能在匹配的滤波模型中获得两种刺激情况下错误响应的可靠近似值。正确响应的数量取决于无噪点图像的轮廓长度和噪声图像的扩展方向轮廓截面的数量。这表明提取与格式塔心理学已知的良好延续定律相关的方向在识别噪声图像中的重要作用。因此,在识别过程的建模中,确定了有噪声的碎片图像和无噪声的碎片图像之间的差异;即,证明了识别对背景或目标环境的依赖性。(C) 2021 年美国光学学会

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