• GHOUSIA B
• RAJESHWARI J

Image Processing is a vital segment of present day advancements since human depends such a great amount on the visual data than many other data. The big challenge to researchers, engineers and specialists is to rapidly separate the significant data from the raw image data. Proposed another strategy for vehicles statistic in complex urban movement scenes to determine insufficiencies of conventional checking strategies, which are profoundly computationally costly and turned out to be unsuccessful with expanding unpredictability in urban rush hour traffic situations. The special feature of the proposed system is it will give more accuracy in normal video and blurred video. This system first applies the de-convolution deblurring techniques on video frames improve the quality of the image and then vehicle counting process is invoked which apply background subtraction and segmentation technique to detect the vehicles. Test results of this system based on real-world urban traffic videos show that the accuracy rate of the proposed approach is very high.

"Statistics on Urban Traffic Vehicles for Real World Videos", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.295-301, June-2018, Available :http://www.jetir.org/papers/JETIR1806547.pdf

"Statistics on Urban Traffic Vehicles for Real World Videos", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp295-301, June-2018, Available at : http://www.jetir.org/papers/JETIR1806547.pdf