Abstract:

In order to solve the difficult problem in car crash experiment to measure and record data, a dynamic image from a car crash detection, target identification and tracking algorithm is proposed. The algorithm uses binary images related to the target and background separation in the region of interest identified targets adjacent frames after the extraction of texture coordinates and feature matching; gives quantitative values of the matching strategy of integration of the weighted average by the criterion of minimizing error rate, etc. fusing the best weights; in the integration of quantitative value is defined as the basis of similarity, by decision threshold between the objectives of the adjacent frames to identify the greatest similarity combinations; which further raised with the same structure mapping principle to determine the best matching target adjacent frames. Experimental results show that the algorithm matching adjacent frames target accuracy than the traditional 5% increase in single\|feature methods, to more effectively track the target.

Key words: vehicle impact, object tracking, nclusive-OR correlation, feature fusion, isomorphic mapping