Welding Inspection using Novel Specularity Features and a One-class SVM
نویسندگان
چکیده
We present a framework for automatic inspection of welding seams based on specular reflections. Therefore, we introduce a novel feature set – called specularity features (SPECs) – describing statistical properties of specular reflections. For classification we use a one-class support-vector approach. The SPECs significantly outperform statistical geometric features and raw pixel intensities, since they capture more complex characteristics and depencies of shape and geometry. We obtain an error rate of 9%, which corresponds to the level of human performance.
منابع مشابه
Optical Inspection of Welding Seams
We present a framework for automatic inspection of welding seams based on specular reflections. To this end, we make use of a feature set – called specularity features (SPECs) – that describes statistical properties of specular reflections. For the classification we use a one-class support-vector approach. We show that the SPECs significantly outperform other approaches since they capture more ...
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