Name
Title | ||
|---|---|---|
High speed road boundary detection on the images for autonomous vehicle with the multi-layer CNN |
Abstract | ||
|---|---|---|
A multi-layer CNN-based algorithm to find the most likely road boundaries on camera images is proposed for the possible application to autonomous vehicle driving. In the previous study, the Dynamic Programming (DP) is shown to be implemented with the multi-layer CNN. If the road-edge images are treated as the space variant distance weights, the optimal path finding algorithm of CNN-based DP can detect the optimal road boundary. Partly disconnected boundary line segments of roads could be linked by way of the most likely road boundary line segments. Fast processing speed is another advantage of the proposed CNN-based structure if it is implemented with hardware circuits. Simulation results about various different road images are included. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ISCAS.2003.1206426 | ISCAS (5) |
Keywords | Field | DocType |
high speed road boundary detection,road vehicles,optimal path finding algorithm,hardware circuits,automatic guided vehicles,camera images,multi-layer cnn-based algorithm,road-edge images,image recognition,edge detection,path planning,cellular neural nets,autonomous vehicle driving,space variant distance weights,dynamic programming,optimal road boundary detection,disconnected boundary line segments,hardware,remotely operated vehicles,image segmentation,mobile robots,cellular neural networks | Motion planning,Line segment,Dynamic programming,Computer vision,Multi layer,Hardware circuits,Computer science,Edge detection,Vehicle driving,Boundary detection,Artificial intelligence | Conference |
Volume | ISBN | Citations |
5 | 0-7803-7761-3 | 1 |
PageRank | References | Authors |
0.48 | 2 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyongsuk Kim | 1 | 500 | 64.95 |
| Seungwan Hong | 2 | 12 | 4.70 |
| Hongrak Son | 3 | 22 | 4.75 |
| Tamás Roska | 4 | 555 | 155.72 |
| F. Werblin | 5 | 15 | 3.88 |