Traffic Sign Recognition

In this paper, the algorithm of Speed Limit Traffic Sign Detection and Recognition will be researched. The system works in two layers: detection and recognition. Sign detection stage finds speed limit sign by using color segmentation combined with shape detection and pixel connectivity; and speed limit sign recognition classifies the speed information inside the sign by using scan-line technique.

4p vilexus 30-09-2022 18 3   Download

The SVM model delivered optimum performance with the radial basis kernel, C=10, and gamma=0.0001. In the proposed method, same priority was given to processing time (testing time) and accuracy, as traffic sign identification is time critical. The final accuracy obtained was 87% (with confidence interval 84%-90%) with a processing time of 0.64s (with confidence interval of 0.57s-0.67s) for correct detection at testing, which emphasizes the effectiveness of the proposed method.

5p spiritedaway36 28-11-2021 10 1   Download

In this paper we chiefly accentuation on the color/shade of the activity sign for its recognition on the grounds that in many spots a standard arrangement of hues are utilized as a part of movement sign like red is used in prohibition signs. In the directional signs blue is the foundation shading in the directional signs and yellow is chosen for warning signs.

7p phanngocminhtam 14-09-2021 9 1   Download

The paper is targeted to apply state-of-the-art algorithms to solve the problem of Traffic Sign Recognition. In doing so, the first solution is detect possible locations of traffic signs from input images. Then, the data used is to be classified, so that two main stages will be focused on, which are feature extraction and classification...

7p trinhthamhodang1218 18-03-2021 10 2   Download

The main features of the TSDR system are real-time processing capability and high accuracy. To achieve these targets, a fusion method which is combination of advanced techniques including adaptive chromatic color segmentation, shape matching, and support vector machine (SVM) is proposed.

11p quilen 30-11-2019 10 0   Download

In this research, we used Convolutional Neural Network [1][2] (CNN) to the task of Traffic Sign Recognition. This research is foundation for us to continue our research on self-driving. Convolutional Neural Network is a multistage architectures. It can be automatically learn features.

7p viengland2711 23-07-2019 16 1   Download

This paper presents the building and the development of a selfpropelled Auto Car mounted camera which has the missions: Lane detection to determine trajectory for the car, traffic sign recognition. The paper also presents the algorithms: CNN model for lane detection, Adaboost for traffic sign recognition.

11p visumika2711 17-07-2019 13 2   Download