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Anthropomorphic OPR method

机译:拟人OPR方法

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摘要

Abstract: Problem of optical pattern recognition (OPR) is sorting numerous images into several subsets. A certain generalized image is ascribed to each subject. For example, the letter 'A,' written in different fonts, to some generalized image of this letter. In this process one has to deprive it of individual attributes i.e. to narrow down its spatial spectrum. This result in a generalized object's image separation with informative fragments (IF) at places with sharp form's changing typical to many similar images. It is shown that in Nature such process can be realized by existing periodic defocusing of the crystalline lens, which leads to generalization of an image projected on the retina. Such process i.e. image defocusing can be used in technique for generalization real images in OPR systems. It was proposed the scheme of possible variant of such robot 'drawing' the generalized images of real objects. The results of computer imitation of 'drawing' generalized images by such a robot, are presented. In report also will be shown an example of possible solving the reverse task: expanding the spatial spectrum of the object with the poor own spectrum for alleviation the problem of its detection (for example, optical feature extractions for target identification). Such procedure according to Shenon's Theory cannot improve the real object's information, but permits alleviate detection of such object. An example of solving one such problem, is presented. !19
机译:摘要:光学模式识别(OPR)的问题是将许多图像分类为几个子集。某个广义图像归因于每个受试者。例如,用不同字体写入的字母'a,',到这封信的一些广义形象。在该过程中,人们必须剥夺个人属性的一个,即缩小其空间谱。这导致通用对象的图像分离与具有尖锐形式的典型变化的地方的信息碎片(IF)与许多类似图像的典型值。结果表明,在自然中,这种方法可以通过结晶透镜的现有周期性灰度来实现,这导致突出在视网膜上的图像的泛化。这样的过程即图像散焦可以用于OPR系统中的泛化真实图像的技术。提出了这种机器人'绘制'的可能变体的方案,该机器人的真实物体的广义图像。呈现了通过这种机器人绘制“绘制”广义图像的计算机模仿的结果。还将在报告中显示可能解决反向任务的一个例子:通过差的自身光谱扩展对象的空间谱来缓解其检测的问题(例如,目标识别的光学特征提取)。根据Shenon理论的这种程序不能改善真实对象的信息,但允许缓解这些对象的检测。介绍了解决一个这样的问题的示例。 !19

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