Appearance-based methods represent a promising research direction to the problem of vehicle detection. These methods learn the characteristics of the vehicle class from a set of training images which capture the variability in vehicle appearance. First, training images are represented by a set of features. Then, the decision boundary between the vehicle and non-vehicle classes is computed by mo...

A typical shadow-eliminating algorithm is presented in this paper. Algorithms for vehicle detection, edge detection and shadow detection are also given. If the shadow is not separated from the vehicle, the next traffic control processes, like vehicle classification, tracking and speed calculation, will be rather difficult. Our approach for shadow processing runs in real time in low-cost hardwar...

The studies in aerial vehicles modeling and control have been increased rapidly recently. In this paper , a coordination of two types of heterogeneous robots , namely unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) is considered. In this paper the UAV plays the role of a virtual leader for the UGVs. The system consists of a vision- based target detection algorithm that uses the ...

the license plate edge detection is the most important step of the process of plate identification. plate recognition system is an automated system that captures vehicle location, vehicle license plate accurately on various vehicles at different times of day and night sets. in this paper the issue of searching the exact location of the license plate from the input images using sobel operator fo...

Vehicle detection has been the critical part of the traffic surveillance system for many years. However, vehicle detection method is still challenging. In this paper, differential morphology closing profile is used to extract the vehicle automatically from the traffic image. Along with closing profile, some addition operation has been applied as a part of the algorithm to get the high detection...

Vehicle detection and annotation for streaming video data with complex scenes is an interesting but challenging task for urban traffic surveillance. In this paper, we present a fast framework of Detection and Annotation for Vehicles (DAVE), which effectively combines vehicle detection and attributes annotation. DAVE consists of two convolutional neural networks (CNNs): a fast vehicle proposal n...

the studies in aerial vehicles modeling and control have been increased rapidly recently. in this paper , a coordination of two types of heterogeneous robots , namely unmanned aerial vehicle (uav) and unmanned ground vehicle (ugv) is considered. in this paper the uav plays the role of a virtual leader for the ugvs. the system consists of a vision- based target detection algorithm that uses the ...

Vehicle detection based on static images are highly practical and directly applicable for vehicle feature extraction and recognition in a traffic surveillance system. This paper will introduce the processing of automatic vehicle detection based on machine learning algorithm. Firstly, Haar-like feature is used to represent the appearance of vehicle, and then a learning algorithm, based on AdaBoo...

Vehicle shadow and superposition have a great influence on the accuracy of vehicles detection in traffic video. Many background models have been proposed and improved to deal with detection moving object. This paper presented a method which improves Gaussian mixture model to get adaptive background. The HSV color space was used to eliminate vehicle shadow, it was based on a computational colour...

This paper describes a vision-based vehicle detection system for a blind spot warning function. This detection system has been designed to provide ample performance as a driving safety support system, while streamlining the image processing algorithm so that it can be processed using the computational power of an existing ECU. The procedure used by the system to detect a vehicle in a blind spot...