3D Surface acquisition and reconstruction for inspection of raw steel products
Computers in Industry - Special issue: Machine vision
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Pattern Recognition
An image content description technique for the inspection of specular objects
EURASIP Journal on Advances in Signal Processing
3D surface acquisition and reconstruction for inspection of raw steel products
Computers in Industry
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This paper proposes coupled hidden Markov models (CHMM) for analysis of steel surfaces containing three-dimensional flaws. Due to scale on the surface, the reflection property across the intact surface changes and intensity imaging fails. Hence, the light sectioning method is used to acquire the surface range data. The steel block is vibrating on the conveyor during data acquisition which complicates the task. After depth map recovery and feature extraction, segments of the surface are classified by means of CHMMs. We present classification results of the CHMM and compare them to the naïve Bayes classifier. The CHMM outperforms the naïve Bayes approach.