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Road crack detection using the particle filter

机译:使用粒子过滤器检测道路裂缝

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摘要

Road crack identification is a prerequisite for both road health monitoring and reduction in reconstruction outlay. This paper proposes a Bayesian approach for pavement crack detection. The task is challenging because there is a small difference between a crack and noise besides the cracks have a strong variance in intensity throughout. The devised solution comprises of three steps. First the image data was acquired from the road imaging system. Second image was preprocessed with the erosion technique. Finally application of a particle filter based geometric model is done. The algorithm has the ability to consider any type of the crack. The method proved to be efficient enough to detect low contrast cracks. Experiments show that the proposed method has better outcomes than most of the prevalent algorithms.
机译:道路裂缝识别是道路健康监测和减少重建费用的前提。本文提出了一种用于路面裂缝检测的贝叶斯方法。这项任务具有挑战性,因为裂缝和噪声之间的差异很小,而且裂缝的强度在整个过程中都有很大的差异。设计的解决方案包括三个步骤。首先,从道路成像系统获取图像数据。用腐蚀技术对第二张图像进行了预处理。最后,完成了基于粒子滤波器的几何模型的应用。该算法可以考虑任何类型的裂纹。该方法被证明足以检测低对比度的裂纹。实验表明,该方法比大多数流行算法具有更好的结果。

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