Crack detection algorithm for fluorescent magnetic particle inspection based on shape and texture features

MA Tao; SUN Zhenguo; CHEN Qiang

doi:10.16511/j.cnki.qhdxxb.2018.22.008

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Journal of Tsinghua University(Science and Technology) ›› 2018, Vol. 58 ›› Issue (1) : 50-54. DOI: 10.16511/j.cnki.qhdxxb.2018.22.008

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Crack detection algorithm for fluorescent magnetic particle inspection based on shape and texture features

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Abstract

This paper introduces an algorithm based on shape and texture features to recognize cracks from fluorescent magnetic particle inspection images. The algorithm detects ridge lines in the images that represent candidate cracks, extracts the local texture features of each ridge point using a scale-invariant feature transform (SIFT) descriptor, and averages those from the same line to form the texture features of the ridge line. A support vector machine classifier is then used to detect the cracks. Tests show that this algorithm more accurately distinguishes the cracks from non-defects than conventional shape-based algorithms or texture-based algorithms. The combined shape and local textures improve the crack detection accuracy.

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fluorescent magnetic particle inspection / image detection / texture feature

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MA Tao, SUN Zhenguo, CHEN Qiang. Crack detection algorithm for fluorescent magnetic particle inspection based on shape and texture features[J]. Journal of Tsinghua University(Science and Technology). 2018, 58(1): 50-54 https://doi.org/10.16511/j.cnki.qhdxxb.2018.22.008

References

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