LED Color Detection of Visual-MIMO System Using Boosting Neural Network Algorithm

LED color detection is a vital part in visual-MIMO system. For deciding transmitted symbols from an LED array image, it is important to detect the color of LED on receiver side. In this paper, we propose a training algorithm, called boosting neural network (BNN) to predict the color of LED on receiver side. First, we take the image of LED array and segment the LED image by using LED detection algorithm. After segmenting the LED image, the LED image is resized in 10 by 10 dimension that means 100 pixels. Each pixel is the input to the BNN model for each RGB color channel. For studying the behavior of each color LED image in low (565 lux) and strong (2450 lux) environmental light intensity, we train our BNN model for low and strong environmental light intensity. Finally, we compare the performance of our BNN model with the regression analysis model at low and strong environmental light intensity. We obtain greater closeness accuracy for each color channel at both environmental light intensities.