• Journal of KIISE:Software and Applications
• /
• v.31 no.11
• /
• pp.1534-1542
• /
• 2004

A novel vision-based scheme of extracting real-time traffic information parameters is presented. The method is based on a region classification followed by a spatio-temporal image analysis. The detection region images for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shadow, using statistical and structural features. Misclassification in a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. Since only local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized without using dedicated parallel processors, while ensuring detection performance robust to the variation of weather conditions, shadows, and traffic load.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.4C
• /
• pp.276-282
• /
• 2005

These studies developed system as well as its algorithm which can measure traffic flow and vehicle speed on the highway as well as road by using industrial television(ITV) system. This algorithm used the real time processing of dynamic images. The processing algorithm of dynamic images is developed and proved its validity by frame grabber. Frame grabber can process the information of a small number of sample points only instead of the whole pixel of the images. In the techniques of this algorithm, we made approximate contour of vehicle by allocating sampling points in cross-direction of image, and recognized top of contour of vehicle. Applying these technique, we measured the number of passing vehicles of one lane as well as multilane. Speed of each vehicle is measured by computing the time difference between a pair of sample points on two sample Points lines.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.1 s.45
• /
• pp.261-267
• /
• 2007

The research about Intelligence Transport Systems(ITS) is actively studied for the traffic problem solution recently. Also, the various methods to detect vehicles moving in the roads are studied. This research using image processing technology is to give the drivers the road information quickly by developing Vehicle Detection System that detects through traffics. Purpose or this research is developing efficient algorithm to facilitate hardware composition. We use morphology method to extract corner points in the images captured by CCD camera. Also, the proposed algorithm detects vehicle's moving area by using motion vectors between corner points. The experiments of the proposed algorithm whose processing time was shortened show good results in vehicle detection on the live road images.

• The KIPS Transactions:PartA
• /
• v.9A no.4
• /
• pp.547-554
• /
• 2002

This paper proposes an efficient dynamic routing algorithm for Multistage Bus Networks(MBN's) in distributed shared memory environment. Our algorithm utilizes extra paths available on MBN and determines routing paths adaptively according to switch traffic in order to distribute traffic among switches. Precisely, a packet is transmitted to the next switch on an extra path having a lighter traffic. As a consequence the proposed algorithm reduces the mean response time and the average number of waiting tasks. The results of simulations, carried out with varying numbers of processors and varying switch sizes, show that the proposed algorithm improves the mean response time by 9% and the average number of waiting tasks by 21.6%, compared to the existing routing algorithms which do not consider extra paths on MBN.

• Journal of Advanced Navigation Technology
• /
• v.9 no.1
• /
• pp.10-18
• /
• 2005

These studies developed system as well as its algorithm which can measure traffic flow and vehicle speed on the highway as well as road by using industrial television(ITV) system. This algorithm used the real time processing of dynamic images. The processing algorithm of dynamic images is developed and proved its validity by frame grabber. Frame grabber can process the information of a small number of sample points only instead of the whole pixel of the images. In the techniques of this algorithm, we made approximate contour of vehicle by allocating sampling points in cross-direction of image, and recognized top of contour of vehicle. Applying these technique, we measured the number of passing vehicles of one lane as well as multilane. Speed of each vehicle is measured by computing the time difference between a pair of sample points on two sample points lines.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.5
• /
• pp.631-637
• /
• 2010

In this paper, We propose a method of motion interpretation of pedestrian for active traffic signal control. We detect pedestrian object in a movie of crosswalk area by using the code book method and acquire contour information. To do this stage fast, we use parallel processing based on CUDA (Compute Unified Device Architecture). And we remove shadow which causes shape distortion of objects. Shadow removed object is judged by using the hilbert scan distance whether to human or noise. If the objects are judged as a human, we analyze pedestrian objects' motion, face area feature, waiting time to decide that they have intetion to across a crosswalk for pdestrians. Traffic signal can be controlled after judgement.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.11
• /
• pp.511-520
• /
• 2016

Automatic License Plate Detection (ALPD) is a key technology for a efficient traffic control. It is used to improve work efficiency in many applications such as toll payment systems and parking and traffic management. Until recently, the hand-crafted features made for image processing are used to detect license plates in most studies. It has the advantage in speed. but can degrade the detection rate with respect to various environmental changes. In this paper, we propose a way to utilize a Faster Region based Convolutional Neural Networks (Faster R-CNN) and a Conventional Convolutional Neural Networks (CNN), which improves the computational speed and is robust against changed environments. The module based on Faster R-CNN is used to detect license plate candidate regions from images and is followed by the module based on CNN to remove False Positives from the candidates. As a result, we achieved a detection rate of 99.94% from images captured under various environments. In addition, the average operating speed is 80ms/image. We implemented a fast and robust Real-Time License Plate Detection System.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.12A
• /
• pp.1922-1931
• /
• 1999

A multicast traffic’s feature is the function of providing a point to multipoints cell transmission, which is emerging from the main function of ATM switch. However, when a conventional point-to-point switch executes a multicast function, the excess load is occurred because unicast cell as well as multicast cell passed the copy network. Additionally, due to the excess load, multicast cells collide with other cells in a switch. Thus a deadlock that losses cells raises, extremely diminishes the performance of switch. An input queued switch also has a defect of the HOL (Head of Line) blocking that less lessens the performance of the switch. In the proposed multicast switch, we use shared memory switch to reduce HOL blocking and deadlock. In order to decrease switch’s complexity and cell's processing time, to improve a throughput, we utilize the method that routes a cell on a separated paths by traffic pattern and the scheduling algorithm that processes a maximum 2N cell at once in the control part. Besides, when cells is congested at an output port, a cell loss probability increases. Thus we use the Output Memory (OM) to reduce the cell loss probability. And we make use of the method that stores the assigned memory (UM, MM) with a cell by a traffic pattern and clears the cell of the Output memory after a fixed saving time to improve the memory utilization rate. The performance of the proposed switch is executed and compared with the conventional policy under the burst traffic condition through both the analysis based on Markov chain and simulation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.31 no.4
• /
• pp.293-300
• /
• 2013

Road signs are important infrastructures for safe and smooth traffic by providing useful information to drivers. It is necessary to establish road sign DB for managing road signs systematically. To provide such DB, manually detection and recognition from imagery can be done. However, it is time and cost consuming. In this study, we proposed algorithms for automatic recognition of direction information in road sign image. Also we developed algorithm code using OpenCV library, and applied it to road sign image. To automatically detect and recognize direction information, we developed program which is composed of various modules such as image enhancement, image binarization, arrow region extraction, interesting point extraction, and template image matching. As a result, we can confirm the possibility of automatic recognition of direction information in road sign image.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.10
• /
• pp.948-956
• /
• 2014

Today, Intelligent Vehicle Detection System seeks to reduce the negative factors, such as accidents over to get the traffic information of existing system. This paper proposes detection algorithm for the illegal U-turn vehicles which can cause critical accident among violations of road traffic laws. We predicted that if calculated optical flow vectors were shown on the illegal U-turn path, they would be cause of the illegal U-turn vehicles. To reduce the high computational complexity, we use the algorithm of pyramid Lucas-Kanade. This algorithm only track the key-points likely corners. Because of the high computational complexity, we detect center lane first through the color information and progressive probabilistic hough transform and apply to the around of center lane. And then we select vectors on illegal U-turn path and calculate reliability to check whether vectors is cause of the illegal U-turn vehicles or not. Finally, In order to evaluate the algorithm, we calculate process time of the type of algorithm and prove that proposed algorithm is efficiently.