Abstract
The tire component of a car is the only one which is in direct contact with the road. They become defective because of factors like driver’s driving, wear out, pressure, overheating, wheel alignment. When the tire is worn, the threads shallow up and can cause the failure of the tires hence reducing safety. A new tire has the capacity of absorbing the heat whereas; the old tire does not absorb the heat and hence is prone to damages. Gray level changes in the image of the tire before and after its surface deformation are found. These changes predict the life of the tire, "more the gray level changes lesser is the life span of the tire and vice-versa". These gray level changes can be found out by using "SVD" The surface deformation of a tire is found by using SVD (Single value decomposition) with PCA(Principal component analysis) algorithm. PCA is used for the sake of Dimensionality Reduction. The principal components depending upon the variance of each training samples and the test samples help in the analysis of its life span. This paper proposes a robust image processing technique developed using the MatLab platform for nondestructive testing of a tire
Published Version
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