Abstract

Some similarity functions for comparing the features of objects in the processing of static images and video sequences are proposed. These functions provide the possibility to find the normalized similarity value and are determined by calculating the ratios between the minimum and maximum values for all the pairs of analyzed features. To find the complex value characterizing the similarity of compared images as a whole, the summation or multiplication of calculated ratios is used. It is proposed to take into account the distances between features for such types of calculations. Some results of experimental studies on the comparison of the qualitative characteristics of similarity functions, their robustness against different types and levels of noises, and the possibility of the precise localization of objects on an image for the case when the brightness levels of pixels are used as features are presented.

中文翻译：

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基于特征间距离和距离计算的图像相似度估计

摘要

提出了一些相似函数，用于比较静态图像和视频序列处理中的对象特征。这些函数提供了找到归一化相似度值的可能性，并通过计算所有已分析特征对的最小值和最大值之间的比率来确定。为了找到表征比较图像整体相似度的复数值，使用了计算比率的求和或相乘。对于这种类型的计算，建议考虑特征之间的距离。关于相似函数的定性特征比较，针对不同类型和水平噪声的鲁棒性的实验研究的一些结果，