IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE-2014), May 09-11, 2014, Jaipur, India Design & Development of Image mosaicling based Intelligent Road Traffc Congestion Control Scheme (IRTCCS) Pardeep Mital Research Scholar Jodhpur National University E-mail: pkm,gagi@gmaiLcom Yash Pal Singh Director, SITM Rewari Alka Nigam Head of Department, ECE Echleon Institute of Technology Faridabad, Abstract- This paper proposes image mosaicking technique for controlling of trafc signals. Limitation of conventional automatic trafc signal control methods is that they can detect the vehicle using sensors, whereas sensors are failed to detect the vehicle, if vehicle is out of range of infrared rays, also sensors are incapable to give response if vehicle stops due to technical problem in the range of infrared rays. This paper proposed an intelligent trafc control method using image mosaicking technique. The striking feature of proposed method is that it measures the density of trafc dynamically .. The efficacy of proposed method has been evaluated, using MATLAB TM Sofware. It is found that proposed method is quite effective for the control of the trafc signals for controlling congestion on the road. Keywords-Image mosaicking; Image Registration; Image Matchin;Traffc Lights. I. [NTRODUCTION Trafc congestion is a major problems encountered in large cities is that of Trafc congestion. For a taveller, congestion means loss of time, missing of opportunities and getting fustation. It also adversely impacts the industies due to productivity loss of the employees, loss of tade opportunities, delayed delivery. Common methods of conventional tafc light contols are time of day contol; fx time contol, area dynamic conol [1]. Artifcial intelligence methods such as ANN [2], Fuzzy Expert system (FES)[3] and [ntelligent decision making system for urban tafc mUTC [4] are reported in literature. However no such a system has developed which meets the adaptive characteristics like the minimum time to take the decision for ON/OFF timings of RGY lights. Traffc density depends on factors like time, day/night, season, weather condition and unpredictable situation such as accidents . If these factors are not taken in to account, the tafc contol system will create congestion collapse. An adaptive tafc contol system must have the ability to fmd saturation conditions in the network and change the objective fnction as required. Conventional tafc conol system use multiple timing plans, whereas advance taffc conol system have multiple conol stategies. The main objective of designing and developing the intelligent road tafc congestion conol simulator is to reduce [978-1-4799-4040-0/14/$31.00 ©2014 IEEE] the waiting time of each lane of vehicles and to maximize the total number of vehicles that can cross the intersections. So [ntelligent road taffc congestion contol scheme is proposed that will measure tafc density on road dynamically and give conol action accordingly. The proposed scheme is illustated in Fig.l. A multiple web cameras of 8.0 Mega pixel has been used in the proposed arangement. However CCTV cameras may be use for better response. Programming sections having GU[ (Graphic User Interface) and Matlab coding. Where GUI is designed for recording/monitoring the video, acquires the image, save the image, process that image, and comparing updated image with test image and Matlab coding sets the timing for each of taffc light (Red, Yellow and Green). [I. BLOCK DIAGARM OF SCHEME Fig. I. Block diagams of congestion control scheme and also matlab coding interfaces or sends the digital data to pins of parallel port. Where [ means +5V and 0 means OV. Depending upon the bits 0 and I set by programming, the hardware receives signal of +5V or OV. Thus this port acts as interface between hardware and sofware. If there is small congestion then timing of Red/Green would be change according to density measured on the road. But in the case of heavy congestion the yellow lights would be blink for indicate collapse.. Multiple cameras has been used in proposed scheme where using image mosaicking technique the data from various cameras are collected and integrated (mosaicking) for matching the two images (test image & reference image) whose result manuplates the timing of green signals/red signals. Proposed work technique is shown in fgure 1 (b).