An Infrared Thermal Image Processing Framework for Defect Detection of a Metal Part with Rough Surface

Jing Xie; Chang Hang Xu; Guo Ming Chen

doi:10.4028/www.scientific.net/AMM.229-231.1356

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Earth Station Tracking SIGSO Satellite: Analysis and Discussion
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 229-231An Infrared Thermal Image Processing Framework for...

An Infrared Thermal Image Processing Framework for Defect Detection of a Metal Part with Rough Surface

Abstract:

We propose an infrared thermal image processing framework based on a modified fuzzy c-means clustering algorithm with revised similarity measure in this paper. The framework can realize the defect detection of a metal part with rough surface. Firstly, a comprehensive method is used to preprocess infrared thermal image. Secondly, the preprocessed image is segmented using modified fuzzy c-means clustering algorithm with revised similarity measure. Finally, taking the average gray level of each cluster in the original gray scale image as a feature, defect cluster is recognized. Experimental result shows that the proposed framework has very promising performance and can obtain precise information of defects on a metal part with rough surface.

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Periodical:

Applied Mechanics and Materials (Volumes 229-231)

Pages:

1356-1360

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.229-231.1356

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Online since:

November 2012

Authors:

Jing Xie, Chang Hang Xu, Guo Ming Chen

Keywords:

Defect Detection, Fuzzy C-Means (FCM), Infrared Thermal Image, Rough Surface, Similarity Measure

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