A Real-Time Vision System for Nighttime Vehicle Detection and Traffic Surveillance

Abstract

This paper presents an effective traffic surveillance system for detecting and tracking moving vehicles in nighttime traffic scenes. The proposed method identifies vehicles by detecting and locating vehicle headlights and taillights using image segmentation and pattern analysis techniques. First, a fast bright-object segmentation process based on automatic multilevel histogram thresholding is applied to effectively extract bright objects of interest. This automatic multilevel thresholding approach provides a robust and adaptable detection system that operates well under various nighttime illumination conditions. The extracted bright objects are then processed by a spatial clustering and tracking procedure that locates and analyzes the spatial and temporal features of vehicle light patterns, and identifies and classifies moving cars and motorbikes in traffic scenes. The proposed real-time vision system has also been implemented and evaluated on a TI DM642 DSP-based embedded platform. The system is set up on elevated platforms to perform traffic surveillance on real highways and urban roads. Experimental results demonstrate that the proposed traffic surveillance approach is feasible and effective for vehicle detection and identification in various nighttime environments.

POSE: Design of Hardware-Friendly Particle-Based Observation Selection PHD Filter

“…unit). Once the products of all particles are collected, C k (z j ) is obtained by (7). The reciprocal of the sum of C k (z j ) and κ k (z) is calculated which then times ψ k,z (x…”

“…Based upon the similar idea of particle filters (PFs) [17], [18], the particle PHD filter uses the sequential Monte Carlo (MC) (SMC) method to approximate the PHD posterior density and can be applied to nonlinear and non-Gaussian MTT problems in denser clutter environments. However, the SMC method has high computational complexity intrinsically and thus limits the usage of the particle PHD filter in real-time industrial applications [7], [19].…”

A Study on Computer Vision Systems for Real-Time Object Detection and Tracking

“…Detection and recognition is very important in intelligent systems [3]. Generally moving object(s) are detected in a video stream as a first step, classified before tracking.…”

Symmetrical Logarithm Transformation Method for Driving Vision Enhancement

“…Low visibility should be blamed in most accidents. To assist car drivers driving smoothly at night, many researches on vehicle detection using vision sensor have been conducted [1][2][3][4]. Due to probable false detection and long processing time, the achievements of these researches are impractical.…”