Detection of Impurity and Bubble Defects in Tire XRay Image Based on Improved Extremum Filter and Locally Adaptivethreshold Binaryzation The manufacturing technology of all steel radial tire is complex. Some defects will inevitably appear in the tire due to the complex production process. Impurity and bubble are two typical kinds of defects in the tire. In this study, a unified detection of impurity and bubble defects in tire Xray images is proposed by means of improved extremum filter and improved locally adaptivethreshold binaryzation . Firstly, the tire image is divided into cords and background by extremum filter. Secondly, an improved locally adaptivethreshold binaryzation is used to separate defects from the background. Finally, image denoising and marking are processed. In the experiment, we tested the proposed approach by using 280 tires with various types of defects from a tire factory. For the detection of clear and blur impurities and clear bubbles, the precision of our method can reach 97%, and the recall is 95.7%. It is to be noted that the proposed method can only be used to detect those two defects in sidewall and shoulder of the tire which we refer as the carcass.

Xray Image Enhancement: A Technique Combination Approach Medical Xray images are an important and valuable source of studies and diagnoses for diseases with low cost besides its high availability. However, radiological images are subject to degradations related to low contrast and presence of noise. Based on this finding, this article presents a simple but efficient enhancement method for these images with the objective of contrast gain and noise removal. The proposed method (MP) consists of a sequence of interactive steps. Start from the step of double precision conversion and end with removing impulsive noises. An evaluation with the PSNR, Entropy, AMBE, and IQR indicators was performed, besides gain check on the thresholding process and the histogram characterization. The evaluation was conducted on three different datasets in a total of 1409 images chest Xrays. The results compared to others known in the literature proved to be promising and put it as an interesting alternative in the process of enhancement medical Xray images.