路面缺陷识别中图像二值化的研究

B. Shumilov, Yuliya Gerasimova, A. Makarov
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引用次数: 4

摘要

物体边界的分配是路面损伤识别的关键问题之一。它们包含关于其形式的详尽信息,以供后续分析。初始图像的二值化方法可以解决这个问题。但这一过程的特点是存在大量的扭曲:洗出、间隙和物体完整性的丧失、均匀区域出现噪声。消除错误的需求导致了大量二值化方法的出现。二值化方法的选择和对一组参数的最优算法的搜索影响着算法在图像分析中的进一步应用。本文考虑了路面损伤识别问题中最流行和最现代的二值化方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Binarization of Images at the Pavement Defects Recognition
Allocation of object borders is the one of the most important tasks at pavement damages recognition. They contain exhaustive information on it's form, for the subsequent analysis. The method of binarization of the initial image copes with this task. But this process is characterized by existence of a large number of distortions: washing out, gaps and loss of objects integrity, emergence of noise in homogeneous areas. Demand of the mistakes elimination has led to emergence of a large count of binarization methods. The choice of a binarization method and search of the optimum (for some set of parameters) algorithm influences the algorithms applied further to the image analysis. In this article we consider the most popular and modern binarization methods concerning problems of recognition of pavement damages.
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