Abstract

The pointer position detection is an important part of implementing the bus dashboard functional test using machine vision. This paper introduces the composition and working principle of the dashboard automatic detection system on machine vision. Then, combining with image processing and Hough transform, we get the image analysis algorithm of the dashboard pointer detection. By analyzing a large amount of computation resulted from the fact that traditional Hough transform uses divergent mapping methods, paper puts forward the methods of improving the convergence of the mapping and conducts parameter space mapping, which effectively reduces the amount of computation. After that, combining with the actual picture of a bus dashboard, automatic detection experiment was carried out for the proposed algorithm. Experiments show that algorithm for dashboard pointer position machine visual based on CM-Hough transform can obtain the angle of the pointer, and effectively shorten the time for dashboard functionality test, and improve the efficiency of the production line for passenger bus dashboard.

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