Automatic Passengers Counting System Using Images Processing Based on YCbCr and HSV Colour Spaces Analysis

Abstract

Public transportations such as trains, commuter, buses, and taxis have become main transportation for major citizen in Malaysia. In recent years, Malaysia’s government has improving a modern public transportation with a big cost such as MRT project and ECRL. In order to improve the public transportation system, the management must propose proper schedule as well as updating the number of passenger counts. In general, the counting process is conducted by manual traditional headcount system which the driver or bus conductor will manually count their passenger. Hence, this process is time consuming. Therefore, this research proposes an automatic passengers counting system using images processing based on YCbCr and HSV colour model analysis. To obtain the passengers counting result, there are several image processing steps to be implemented; (1) data collection by capturing 50 passenger images, (2) colour conversion from RGB to YCbCr and HSV colour spaces, (3) image segmentation using Otsu thresholding method, (4) removing of unwanted object and, (5) passenger counting process. This study will analyze two different colour conversions which are from RGB to HSV, as well as from RGB to YCbCr colour conversion. Overall, segmentation using HSV colour model has proven to be the best in segmenting the passenger’s image with segmentation accuracy of 85.63%. Overall, this project is expected to help buses administration to improve their services by updating their passengers counting automatically.