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

Bondarko, V.M., Chikhman, V.N.

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Publication in Journal of Optical Technology

For Russian citation (Opticheskii Zhurnal):

Бондарко В.М., Чихман В.Н. Различия в опознании фрагментированных зашумлённых и незашумлённых изображений, выявленные при моделировании // Оптический журнал. 2020. Т. 87. № 10. С. 15–24. http://doi.org/10.17586/1023-5086-2020-87-10-15-24 Bondarko V. M. and Chikhman V. N. Differences in recognition of fragmented noisy and non-noisy images revealed by modeling [in Russian] // Opticheskii Zhurnal. 2020. V. 87. № 10. P. 15–24. http://doi.org/10.17586/1023-5086-2020-87-10-15-24

For citation (Journal of Optical Technology):

V. M. Bondarko and V. N. Chikhman, "Differences in recognition of fragmented noisy and non-noisy images revealed by modeling," Journal of Optical Technology. 87(10), 574-580 (2020). https://doi.org/10.1364/JOT.87.000574

Abstract:

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.

Keywords:

identification of fragmented images, identification errors, modeling, spatio-frequency analysis, image features

OCIS codes: 330.7326, 330.4060, 330.5510

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