Image processing applications started in 1921 and the main focus was on developing devices which could manage to capture high resolution images. Since this time, there have been various digital images processing techniques which have been researched or various applications. These aspects have all been made possible through the use of computer graphics. Computer Graphics has developed through the ages to become a mature discipline which is built on strong mathematical basis and with applications in an ever increasing number of areas. The use of Information Technology has played a very significant role in aiding the performance of several operations in our day to day activities. Several countries in the world have been able to use Information technology to monitor their traffic systems and ensure that there is a proper monitoring of their traffic. There are several advantages and disadvantages which come with this new emerging technology. It employs the use of cameras to capture the traffic information and report the results to the relevant authorities. Several literatures have been put forward concerning this system. Scholars have different approach towards this scenario as shown below.
Researchers have been involved in a series of research technologies in order to determine the best methods that can be used for monitoring traffic conditions.
Kai She, George Bebis, Haisong Gu and Ronald Miller proposed a need for more reliable traffic data acquisition than the localized methods of data collection which is generated by traditional loop detectors.
Mao-Chi Huang and Shwu-Huey Yen, suggested a system that can be used for extracting information about a vehicle’s speed and direction. This system generates descriptions of movement with specified regions on the road. However, the system does not generate information about the size of a vehicle, its shape or the number of vehicles on the road at any particular time. Harlow and Peng on their research described several methods that can be used for processing range imagery and for performing vehicle detection and classification. This was a major break-through in terms of getting more information about a vehicle on the road. Xin Li et al., also presented an overview of image processing and tools for analyzing traffic applications on traffic monitoring and automatic vehicle guidance. Georgina, Kien and Rui considered the advantages of employing internet-connected to enhance e-transportation with the ability to respond to terrorist threats and other human caused disasters. They found surface transportation to be of critical importance in responding very fast to various kinds of human caused disasters. The significance of their research consisted of enhancing the surface transportation aspects.
Sam Tran and M.S and T.A Yang have developed a method called Optimized Communication and Organization (OCO) method which enables efficient target tracking in wireless sensor networks. They also managed to develop Optimized Computation and energy dissipation to maximize the lifetime of the sensor network.
The main aim/objective of the research was to come up with a mechanism or a system which could ensure an accurate monitoring and taking records of traffic. The research is also aimed at providing a better roads maintenance mechanism which can save the road user a lot of time wasted on the roads due to traffic jams. This research is also going to take into consideration the way accidents are recorded and ways of reducing the accidents.
There are several methods that can be used when carrying out this research. The most common method that we are going to use when carrying out the research is going to use the existing literature so as to design a system that will be used in implementing our system. Other methods that can be used when carrying out the research can involve engaging the traffic policemen in a series of question and answers so as to ascertain the situation on roads.
1. Sam Tran Phu Manh, M.S., T. A. Yang," Applying Image Processing Techniques to Simulate a Self-Organized Sensor Network For tracking objecs" The University of Houston Clear Lake, 2005
2. Georgiana L. Hamza-Lup a, Kien A. Hua b, Rui Peng b "Leveraging e-transportation in real time traffic evacuation management ", a Department of Computer Science and Engineering, Florida Atlantic University, 500NW California Blvd., Port St. Lucie, FL 34986, USA , b School of Computer Science, University of Central Florida, USA , 6 December 2006
3. Mao-Chi Huang and Shwu-Huey Yen, “A real-time and color-based Computer Vision for Traffic Monitoring System”. IEEE International Conference on Multimedia and Expo (ICME), 2004.
4. Xin Li, XiaoCao Yao, Yi L.Murphey, Robert Karlsen and Grant Gerhart, “A real-time Vehicle Detection and Tracking System in Outdoor Traffic Scenes”. Proceedings of the 17th International Conference on Pattern Recognition (ICPR), 2004.
5. Koller, D, Weber, J, Huang, T, Malik, J, Ogasawara, G, Rao, B, Russell, “Towards robust automatic traffic scene analysis in real-time”. ICPR, Israel, Vol 1, pp 126-131, 1994.
6. Kai She, George Bebis, Haisong Gu and Ronald Miller, “Vehicle Tracking Using on-line Fusion of Color