Automatic Detection of Defects in Tire Radiographic Images

This paper is about the detection of tire defects in multi-textural radiographic images. We consider the tire defects characterization problem in ways of local regularity analysis and scale characteristic. Optimal scale and threshold parameters are selected using a defect edge measurement model to frame defect edge detection. This framework distinguishes the defects from the background textures. Finally, a novel method for detection of tire defects is proposed based on wavelet multiscale analysis. We provide examples with a consistent dataset of 400 images selected over 3700 industrial images in order to illustrate and validate the obtained results which demonstrate substantial improvement over the state of the art.