Front Vehicle Identification Algorithm Based on Visual and Multi-feature

Existing algorithms of video vehicle detection can be affected by light,noise and other environmental factors with high missed and false detection rate,and it is also difficult to meet robust and real-time,a complete algorithm of front vehicle detection was presented.On the basis of the improved Hough transform extracting the lane,this algorithm first processed the image by adaptive binarization,filtering out interference point through method of corrosion and expansion.Shaded area was merged and the ROI was extracted in simple and effective way.This algorithm could utilize entropy and rear symmetry characteristics to screen and discern the ROI area,reducing the missing and false detection rate.Good results were achieved by using Robinson-direction detection operator to extract the boundary of vehicle.Resultsshow that when the video has a resolution of 640×480 pixels,the correct recognition rate has achieved 89.4%,and there will be 17.65 frame to be processed within per second.