Tire Defect Detection Using Image Component Decomposition

This study presents a component decomposition based method for fast tire defect detection, which is motivated by the fact that defective tire images mainly consist of three components: texture, background and defect. Thus the proposed method exploits three steps to separate the defect component from the defective image. At the first step, the local total variation filtering is used to extract the texture. Then the background is estimated by the vertical mean filtering. Finally, the defect is detected by thresholding the residual image. Experimental results show that the proposed method is more accurate in locating the defects.