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The following topics are dealt with: linear approximation; license plate recognition; color image segmentation; image quantization; wireless video transmission; congestion control; stochastic search; transmembrane helical segments; wavelet transform; semisupervised cluster algorithm; anomaly detection; data privacy; online market information processing; user behavior; particle swarm optimization;...
Pedestrian detection is one of the most popular research areas in video processing and it is vital for video surveillance systems. In this paper, we present a real-time pedestrian detection system based on Dalal and Triggs's human detection framework with the use of image segmentation and virtual mask. Image segmentation enables the system to focus only on the region of interest whereas the virtual...
The application of edge detection to obtain salient lane boundaries on road image is popular in the computer vision area. However, edge detectors may be easily distracted by manifold noises that emerged on the road surface such as shadow cast, vehicles or other obstacles. Additionally, sky region can adversely affect the performance of lane detection method due to the presence of horizontal edges...
Focusing on the problem that the detection accuracy of traffic detection system is sensitive to the changes of complex environments, this paper presents an improved method of vehicle detection. It builds and updates the background adaptively. Additionally, to improve the computation efficiency of shadow elimination, a fast algorithm of neighbor mean based on HSV model is proposed. As the occlusion...
This paper analyzes the basic method of digital video image processing, studies the vehicle license plate recognition system based on image processing in intelligent transport system, presents a character recognition approach based on neural network perceptron to solve the vehicle license plate recognition in real-time traffic flow. Experimental results show that the approach can achieve better positioning...
In order to improve the accuracy of vehicle detection, and to solve the gradually changing brightness of light in the background and the movement of the objects in the background, this paper presents an algorithm that fast adapts to the background generation and updating. Focus on the objects with similar gray background, and moving object missing caused easily by segmentation, the threshold segmentation...
Traffic number recognition is the important and essential content on license plate recognition and traffic sign recognition. A method of traffic number recognition based on the neural network and the invariant moments was proposed in this paper. Firstly, the area of the traffic number was located from the complicated image background and each number was taken by the image segmentation. Secondly, the...
There are some usual methods in vehicle license plate location, such as segmentation in grey-level image, color image edge extraction and neural networks filters etc. All these methods are proved not quite satisfactory in various conditions, or are influenced by some factors. In this paper, we present to classify colors of pixels by using improved neural networks, which include 27 nodes of input layer,...
Our goal is to detect and track moving vehicles on a road observed from cameras placed on poles or buildings. Inter-vehicle occlusion is significant under these conditions and traditional blob tracking methods is unable to separate the vehicles in the merged blobs. We use vehicle shape models, in addition to camera calibration and ground plane knowledge, to detect, track and classify moving vehicles...
This paper aims to present three new methods for color detection and segmentation of road signs. The images are taken by a digital camera mounted in a car. The RGB images are converted into IHLS color space, and new methods are applied to extract the colors of the road signs under consideration. The methods are tested on hundreds of outdoor images in different light conditions, and they show high...
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