Road sign recognition for assisting drivers
For a highly reliable autonomous vehicle, it must be able to detect traffic signs and obey the traffic rules. In this paper, color segmentation is applied in YCbCr color space and shape detection is processed through blob analysis method. By calculating the circularity and area ratio with bounding b...
Saved in:
主要作者: | |
---|---|
其他作者: | |
格式: | Final Year Project |
語言: | English |
出版: |
2016
|
主題: | |
在線閱讀: | http://hdl.handle.net/10356/67956 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
總結: | For a highly reliable autonomous vehicle, it must be able to detect traffic signs and obey the traffic rules. In this paper, color segmentation is applied in YCbCr color space and shape detection is processed through blob analysis method. By calculating the circularity and area ratio with bounding box, the shapes in binary images can be classified accurately. In the recognition stage, SURF algorithm is performed on both the training sets and sample images to extract the features points of the traffic signs for matching based on K-NN classifier. |
---|