Speed Limit Detection and Lane Departure Warning Based on Computer Vision
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 spe...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2017
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| Online Access: | http://ndltd.ncl.edu.tw/handle/40505667216279969540 |
| Summary: | 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.
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