Two-stage racetrack segmentation method using color feature filtering and superpixel-based convolutional neural network

Publication Name: Saci 2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2018-08-20

Volume: Unknown

Issue: Unknown

Page Range: 131-135

Description:

The Széchenyi István University race car team is an active and successful participant of the Shell Eco-marathon for long time ago. The Shell introduces the autonomous vehicle category on the Eco-marathon for 2018. Our long-term goal is to make the Szenergy racing team's vehicle suitable for the autonomous category. The first milestone is to make a reliable computer vision based intelligent detection system that understands the environment of the racing car. In this paper we will present a solution for racetrack detection i.e. a fusion of image processing and neural network systems. The two-stage recognition system is at the first phase an image processing algorithm which finds the red-white and blue-white striped edge of the road, and at the second phase, a pre-trained superpixel-based neural network which recognize the road on the filtered image.

Open Access: Yes

DOI: 10.1109/SACI.2018.8440968

Authors - 3