面向梯度的相干向量神经网络交通标志识别

The 2011 International Joint Conference on Neural Networks Pub Date : 2011-10-03 DOI:10.1109/IJCNN.2011.6033318

Reghunadhan Rajesh, K. Rajeev, K. Suchithra, L. V. Prabhu, Vignesh Gopakumar, N. Ragesh

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引用次数: 21

摘要

本文利用定向梯度相干向量(CVOG)进行交通标志识别。在德国交通标志基准数据集上进行了实验。基于CVOG特征的神经网络分类器在交通标志识别方面取得了良好的效果。结合其他特征得到的结果识别率更高。

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Coherence vector of Oriented Gradients for traffic sign recognition using Neural Networks

This paper makes use of Coherence Vector of Oriented Gradients (CVOG) for traffic sign recognition. Experiments are conducted on German Traffic Sign benchmark dataset. The results on traffic sign recognition using CVOG features with neural network classifier is promising. The results based on the combination of other features gave better recognition rates.

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The 2011 International Joint Conference on Neural Networks

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