Traffic Light Detection Using Back Propagation Neural Networks in Thailand
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Abstract
This paper proposes a traffic lights detection method using back propagation neural network at the day-time. In the first step, traffic lights image are extracted from RGB color image. Input RGB image is transformed into Ycbcr color space, then red and green color dominant regions are selected as candidates. And, the final step, back propagation neural network applied for red color recognizes. For experimental result, a 3-layered back propagation neural network is applied to detect and determine the parts of a traffic light useful for detection. Experiments the accuracy of the method is shown and is compared with that by the k-nearest neighbor classification.
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