Improving the accuracy of estimating the measure of proximity between objects during recognition

S.Y. Aliyeva
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Abstract

The article analyzes the problem of the occurrence of errors in measuring the geometric parameters of objects in pattern recognition, possible ways to minimize them, and as a result of this analysis, an algorithm is proposed for effectively increasing the reliability of pattern recognition by adequately estimating the measure of proximity between recognized and standard objects. The article considers a model for the process of estimating the measure of proximity between objects and the resulting errors, proposes conditions and an algorithm for minimizing these errors, and recommends measures to improve the accuracy of estimating the measure of proximity between objects.
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提高识别过程中估计目标间接近度量的准确性
本文分析了模式识别中物体几何参数测量误差的产生问题,提出了一种通过充分估计被识别物体与标准物体之间的接近度来有效提高模式识别可靠性的算法。本文考虑了一种估算目标间接近度量过程的模型及其产生的误差,提出了使这些误差最小化的条件和算法,并提出了提高目标间接近度量估计精度的措施。
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