Grouping Beamlet Transform for Surface Crack Detection

Tian Cai, Weiwei Zhao, Zhe Lin, Pengfei Guo
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Abstract

Beamlet transform is an excellent multiscale geometric analysis method. It has a great capacity of extracting line features from images under noise. However, it is too slow since a mass of redundant beamlets waste much time. In fact, only several of them are helpful in many applications. In this paper, grouping beamlet transform is presented to fasten line feature detection for surface crack detection. Geometric flows used in grouplet transform are introduced to determine geometric structures of an image. In each recursively partitioned box, only the beamlets along with major direction are generated. So that lots of useless beamlets for the image can be excluded from the following integral computation. Experiments on various optical images show that grouping beamlet transform is able to detect line features in an image the same as classic beamlet transform, however, the former runs much faster than the latter on any of the tested images. In some cases, only about 60% of consuming time in classic beamlet transform may be needed in grouping beamlet transform. As an improvement of beamlet transform, grouping beamlet transform will be more applicable in the field of surface crack detection.
基于分组波束变换的表面裂纹检测
束波变换是一种优秀的多尺度几何分析方法。该算法具有较强的噪声条件下的图像线特征提取能力。然而,由于大量的冗余光束浪费了大量的时间,它的速度太慢了。事实上,在许多应用程序中,只有其中几个是有用的。提出了一种基于分组小波变换的表面裂纹线特征检测方法。介绍了利用群态变换中的几何流来确定图像的几何结构。在每个递归分区的盒子中,只生成主方向的光束。这样就可以在接下来的积分计算中排除大量对图像无用的光束。在各种光学图像上的实验表明,分组波束变换与经典波束变换一样能够检测图像中的线特征,但前者在任何被测试图像上的运行速度都比后者快得多。在某些情况下,分组波束变换只需要传统波束变换60%左右的时间。分组波束变换是对波束变换的一种改进,将更适用于表面裂纹检测领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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