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Pedestrian detection is an important research field in advanced driver assistance system (ADAS). This paper puts forward a pedestrian detection framework based on both heuristic statistics and machine learning. First, a restriction of region of interest (ROI) is set on the captured image. Second, the template matching coarsely detects candidate pedestrians by using a set of template images, the edge...
Against lots of conventional vertical-edge-based License Plate Detection (LPD) systems, this paper presents a robust and real-time LPD system to differentiate the strength and density of vertical edges between the license plate region and non-plate regions. The proposed LPD system consisting of 2-level 2D Haar Wavelet transform and Wiener-deconvolution vertical edge enhancement not only can highlight...
The objective of the paper is to implement a system which effectively reduces vehicle collisions by using a combination of image processing and neuro-fuzzy based techniques. It uses an image processing module in order to determine the distance of the front vehicle. The distance measurements are given to a sugeno type adaptive neuro-fuzzy system. Since the operation of the system is mission critical...
This paper presents a new framework and feature set for vehicle model query system. By giving model names or manufacturer names as keywords, the desired vehicle images can be queried from target videos or vehicle image databases using internet-vision approach. In this framework, sample images are automatically retrieved from internet via search engine or car related website. Logos and frontal masks...
In this paper, we propose a vision-based robust vehicle distance estimation algorithm that supports motorists to rapidly perceive relative distance of oncoming and passing vehicles thereby minimizing the risk of hazardous circumstances. And, as it is expected, the silhouettes of background stationary objects may appear in the motion scene, which pop-up due to motion of the camera, which is mounted...
This paper is dedicated to a license plate recognition (LPR) system for moving vehicles by using car video camera. The proposed LPR method mainly consists of preprocessing, plate location, and character segmentation & recognition. At irst, the possible regions of license plate are enhanced from the captured images through the proposed edge detection method and gradient-based binarization....
Road conditions can provide important information for driving safety in driving assistance system. The input images usually include unnecessary information and road conditions need to be analyzed only in a region of interest (ROI) to reduce the amount of computation. In this paper, a vision-based road ROI determination algorithm is proposed to detect the road region using the positional information...
The Hough transform is a well-known straight line detection algorithm and it has been widely used for many lane detection algorithms. However, its real-time operation is not guaranteed due to its high computational complexity. In this paper, we designed a Hough transform hardware accelerator on FPGA to process it in real time. Its FPGA logic area usage was reduced by limiting the angles of the lines...
In this paper we present an autonomous car with distributed data processing. The car is controlled by a plurality of independent sensors. For the lane detection, a camera is used, which detects the lane marks with a Hough transformation. Once the camera detects these, one of them is calculated to be followed by the car. This lane is processed in connection with the information of the other sensors...
Vehicle Plate Recognition (VPR) algorithm in images and videos usually consists of the following three steps: 1) Region extraction of the plate (plate localization), 2) characters segmentation of the plate 3) Recognition of each character. This paper presents new methods for real-time plate recognition in each step. We used a Detector for the Blue Area (DBA) to locate the plate, Averaging of White...
Aerial imagery sensors can provide sufficient resolution to sense vehicle locations and movements across broader spatial and temporal scales. In this paper, an approach for collecting and analyzing aerial imagery is given. This paper presents a method to detect vehicle from a moving camera. The detection component involves a cascade of modules. First, road is detected Based on edge detection and blob...
This paper presents a method for estimating the current lane number in which the vehicle is traveling. An important component of visual automobile safety systems rely on knowledge of the lane number to know how far the vehicle is from the exit lane. The method uses taking the Inverse Perspective Map of an image to get a top view of the road and then detects multiple lanes using Hough transform line...
The current vehicle tracking algorithms cannot meet the requirements of high robustness in engineering application. A co-training algorithm based on on-line boosting for vehicle tracking is proposed. In this algorithm, first the vehicle region of interest is detected by vehicle-shadow feature and vehicle horizontal edge feature. Then the vehicle region of interest is verified by off-line classifiers...
This paper introduces a vehicle detection method based on multi-scale active basis model in traffic surveillance systems. Due to the effects of perspective, vehicles which are close to the camera are larger and more detailed than the far ones on individual video frames. Using camera calibration, we get the multi-scale information of vehicles, and then we learn the multi-scale active basis model from...
In complex urban traffic conditions, the accurate detection of vehicles is challenging to current vehicle detection methods. To achieve the precise vehicle detection in complex urban traffic conditions, we have proposed a vehicle detection method based on a deformable hybrid image template in this paper. Our method contains two steps: constructing our hybrid image template and its probability model,...
In complex urban traffic conditions, occlusion between vehicles is a common problem which is challenging to current vehicle detection methods. In this paper, we have proposed a vehicle detection method based on a part-based model which can deal with the occlusion problem. Our method includes two steps: constructing the part-based model and detecting vehicles from traffic images. In the first step,...
This paper aims to present a new approach to detect traffic signs which is based on color segmentation using AdaBoost binary classifier and circular Hough Transform. The Adaboost classifier was trained to segment traffic signs images according to the desired color. A voting mechanism was invoked to establish a property curve for each of the candidates. SVM classifier was trained to classify the property...
Vehicle Detection is an important part in intelligent transportation system (ITS) and driver assistance system. Considering vehicles have strong edges and lines in different orientation and scales, in this paper, we presents a method for detecting vehicles based on a feature named Pyramid Histogram of Oriented Gradient. This feature provides spatial distribution information of edges which was often...
In this paper, a novel license plate detection method is proposed. There are three key steps in our method, i.e. image preprocessing, license plate detection and license plate confirmation. First, the noises are removed and the diversities of license plate forms are unified through image preprocessing. And then, the license plates are detected roughly by using the cascade AdaBoost classifier. Finally,...
With the progress of science technology and the vehicle industry, there are more and more vehicles on the road. As a result, the heavy traffic often leads to more and more traffic accidents. In common traffic accident, the driver's inattention is usually a main reason. To avoid this situation, this paper proposes a sleepy eye's recognition system for drowsiness detection. First, a cascaded Adaboost...
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