| Summary: | 碩士 === 淡江大學 === 土木工程學系 === 84 === In this thesis, we try to develop an algorithm to detect
turning parameters of vehicles in intersection. We track twelve
directions of vehicular movement and classify three kinds of
vehicle type. Our approach consist of the following main steps:
First, we use Sobel filter to find the edge. Then, we extract
the contour of cars with dilation and erosion procedures. In
order to avoid the aperture problem and acquire accurate optical
flow estimation, the optical flow vectors are computed only on
the image patch centered at corners. After that, we clustered
the optical flow which belongs to the same vehicle by its blob
image. Then we can track its position via velocity field. The
detection system can output four parameters including
trajectory, vehicle type, traffic volume and speed. A case study
was demonstrated through this technique with relatively
satisfactory identification rate of 92.65 in passenger cars.
About flow, accurate rates of go straight trucks is 80.00%,
passenger cars is 92.68%, motorcycles is 87.50%. Accurate rates
of left turn passenger cars is 90.48%, motorcycles is 80.00% and
there is no error occur about right turn passenger cars. The
error of speed is about 6.86%. The performance of the
algorithm,though,is fine,but it needs more cases to calibrate.
After do that, we can finally give judgement on the algorithm.
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