Abstract

The article presents the results of research on development of a method for calculating human operator recognition probability of objects noisy images generated by optoelectronic surveillance devices. The proposed method is based on a visual system mathematical model which takes into account features of pre-processing images performed in human eyes as well as at stages of primary and secondary processing performed in the visual cortex of the brain. Experimental studies on image recognition of halftone objects confirmed the adequacy of the visual system mathematical model and the calculation method based on this model are described.

中文翻译：

---

计算人对物体图像识别概率的方法

摘要

本文介绍了开发一种计算人类操作员识别光电监控设备生成的物体噪声图像的概率的方法的研究结果。所提出的方法基于视觉系统数学模型，该模型考虑了在人眼中执行的预处理图像以及在大脑视觉皮层中执行的初级和次级处理阶段的特征。描述了半色调对象图像识别的实验研究，证实了视觉系统数学模型的充分性，并描述了基于该模型的计算方法。