Smart Vision System for Car Tire Condition Monitoring

Car tire failure is one of the major causes of serious accident. To reduce the accidents, the US National Highway Transport Safety Administration (US NHTSA) has passed a legislation requiring all new passenger cars to be equipped with Tire Pressure Monitoring System (TPMS) starting from November 2006. However, according to automotive experts, tire failure could also originate from excessive tread wear and other several causes. This research project is proposed to analyze tire tread conditions, and relay the information back to the user. The project is a software that is developed using Matrox Imaging Library and Visual Basic Version 6 (VB6). It consists of an inference engine, image files, selected Matrox Imaging Library modules and a graphical user interface module. The software employs an automatic threshold value selection method, that is developed during this project, to binarize a tire tread image before analyze it. The result shows that the new automatic threshold value selection method is able to binarize an image better than the “Binarize” method that is available in Matrox Imaging Library. The proposed system uses the “Blob Analysis” module that is available in Matrox Imaging Library to analyze a tire tread image that was binarized. The system is able to categorize an image into seven conditions i.e. worst, bad, over limit, on the limit, nearly reaches limit, beginning and good conditions, instead of only bad and good conditions. The proposed system applies If-Then rules in blob analysis stage. Moreover, the monitoring system is able to point out the abnormal tread wear location in an image using colored rectangular lines. The system is also able to advice an action needed to be taken by the user. Based on the test results, the proposed system is able to detect and monitor several types of tire tread wear i.e. abnormal tread wear due to chamber alignment problem, abnormal tread wear due to improper inflation, abnormal tread wear due to excessive usage and normal tread wear. The proposed system is also able to analyze all sizes of tires and various types of tread patterns produced by various manufacturers.

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