Speed Limit Detection and Lane Departure Warning Based on Computer Vision

• Main Authors: Sheng-Tang Chang, 張盛唐
• Other Authors: Chang-Ming Wu
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/40505667216279969540

碩士 === 中原大學 === 電子工程研究所 === 105 === Advanced driver assistance system is focused on the process of the electronic vehicle. It is a very important research direction of the organisms. We use the RADAR and LiDAR to measure the distance between the obstacles and the speed of the vehicle in the high speed driving situations. The sensors are high price and impermissible. In our thesis, we study and develop the speed limit sign identifying system and lane departure warning system based on the methodologies of the computer vision. In the speed limit sign identifying system, we use the edge gradient to find the Hough circle contours of the picture. We get the histograms of oriented gradients in the circle area, and extract the features from the histograms. The features can be used to train and classify the support vector machines. We determine the speed sign and the speed number from the trained support vector machines. We find the straight line by the Hough transform in the picture. We can determine the lane departure of the vehicle. We tested the identifying system and warning system in the day and night. The results of the identification almost are the same. It takes about 0.1 seconds from getting image to the results. The correction of the speed sign detection is about 92%. The correction of the speed number recognition is 87%. And it takes about 0.04 seconds to detect lane offset.