Approaches of computing traffic load for automated traffic signal control: A survey

Abstract

Traffic images captured using CCTV camera can be used to compute traffic load. This document presents a survey of the research works related to image processing, traffic load, and the technologies used to re-solve this issue. Results of the implementation of two approaches: morphology-based segmentation and edge detection using sobel operator, which are close to traffic load computation have been shown. Segmentation is the process of partitioning a digital image into its constituent parts or objects or regions. These regions share common characteristics based on color, intensity, texture, etc. The first step in image analysis is to segment an image based on discontinuity detection technique (Edge-based) or similarity detection technique (Region-based).Morphological operators are tools that affect the shape and boundaries of regions in the image. Starting with dilation and erosion, the typical morphological operation involves an image and a structure element. The edge detection consists of creating a binary image from a grayscale image where the pixels in the binary image are turned off or on depending on whether they belong to region boundaries or not. Image processing is considered as an attractive and flexible technique for automatic analysis of road traffic scenes for the measurement and data collection of road traffic parameters. Combined background differencing and edge detection and segmentation techniques are used to detect vehicles and measure various traffic parameters. Real-time measurement and analysis of road traffic flow parameters such as volume, speed and queue are increasingly required for traffic control and management.