Vehicle classification through detection and color segmentation of registration plates running on raspberry Pi 3 model B

Abstract

Classification of license plates provides useful information regarding the nature of the vehicle, whether it is used for public transport, a privately-owned vehicle, an official vehicle, or a special vehicle. In the Philippines, the registration plates of vehicles are classified by colors. Colors such as red, green blue, black, yellow are used to identify what vehicle classification the plate belongs to. The information is useful to applications in statistics and transport regulation. This paper discusses a convolutional neural network based embedded system that runs on Raspberry Pi 3 Model B. The said system provides a process of classifying vehicles using plate detection using Convolutional Neural Networks and color thresholding of registration plates using the RGB color space. TensorFlow and OpenCV libraries were utilized for the detection and classification.