Traffic Density Measurement using Image Processing: An SVM approach

Author(s):  
Hosne-Al-Walid, Nafisa Anjum
IJIREEICE ◽  
2017 ◽  
Vol 5 (5) ◽  
pp. 319-324
Author(s):  
Mrs. Harshitha R ◽  
Chandan R ◽  
Poornima K ◽  
Navyashree U N ◽  
Sandesh Gowda P

Author(s):  
Se-Hwan Chi ◽  
Cristian I. Contescu ◽  
Timothy D. Burchell

The strong correlation between the density and the physical and, mechanical properties of graphite suggests that the method of nondestructive density evaluation could be developed into a characterization technique of great value for the overall improvement of safety of graphite moderator reactors. In this study, the oxidation-induced density changes in nuclear graphite for VHTR were determined by a conventional destructive bulk density measurement method (BM), and by a new non-destructive method based on acoustic microscopy and image processing (AM). The results were compared in order to validate the applicability of the latter method. For a direct comparison of the results from both measurements, two specimens were prepared from a cylindrical graphite sample (1 inch diameter and 1 inch height, oxidized to 10% weight loss at 973 K in air for 5 hours). The specimens were used for characterization by BM and AM methods, respectively. The results show that, even with a large standard deviation of the AM, the density changing trend from both methods appeared the same. This observation may be attributed to the fact that AM images reflect characteristic density changes of the graphite sample through the acoustic impedance changes. This study demonstrates the possibility of using AM as a nondestructive technique for the evaluation of density changes in graphite when a database is prepared through a systematic series of experiments.


Author(s):  
Se-Hwan Chi ◽  
Cristian I. Contescu ◽  
Timothy D. Burchell

The strong correlation between the density and the physical and mechanical properties of graphite suggests that the method of nondestructive density evaluation could be developed into a characterization technique of great value for the overall improvement of the safety of graphite moderator reactors. In this study, the oxidation-induced density changes in nuclear graphite for very high temperature reactor were determined by a conventional destructive bulk density measurement method (BM) and by a new nondestructive method based on acoustic microscopy and image processing (AM). The results were compared in order to validate the applicability of the latter method. For a direct comparison of the results from both measurements, two specimens were prepared from a cylindrical graphite sample (1 in. diameter and 1 in. height, oxidized to 10% weight loss at 973 K in air for 5 h). The specimens were used for characterization by BM and AM methods, respectively. The results show that, even with a large standard deviation of the AM, the density changing trend from both methods appeared the same. The present observation may be attributed to the fact that AM images reflect characteristic density changes of the graphite sample through the acoustic impedance changes. This study demonstrates the possibility of using AM as a nondestructive technique for the evaluation of density changes in graphite when a database is prepared through a systematic series of experiments.


2017 ◽  
Vol 162 (10) ◽  
pp. 8-12 ◽  
Author(s):  
Alisha Janrao ◽  
Mudit Gupta ◽  
Divya Chandwani ◽  
U. A.

Author(s):  
Lakshmanan M, Et. al.

Traffic congestion at junctions is a serious issue on a daily basis. The prevailing traffic light controllers are unable to manage the different traffic flows. Most of the current systems operate on a timing mechanism that changes the signal after a particular interval of time. This may cause frustration and result in motorist's time waste. Traffic congestion is a major problem in the currently existing systems. Delays, safety, parking, and environmental problems are the main issues of current traffic systems that emit smoke and contribute to increasing Global Warming. Sensor-based systems reduce the waiting time and maximize the total number of vehicles that can cross an intersection. Our proposed system can control the traffic lights based on image processing without the need for traffic police. This can reduce congestion, delay, road accidents, need for manpower. Under image processing, we use sub techniques like RGB to Gray conversion, Image resizing, Image Enhancement, Edge detection, Image matching, and Timing allocation. A real-time image is captured for every 1 second. After edge detection procedure for both reference and real-time images, these images are compared using SURF Algorithm. Then the amount of traffic is detected and the details are stored in the server. Arduino is used for a traffic signal in the hardware part. It consists of a Wi-Fi module. The micro-controller used in the system Arduino. Four cameras are placed on respective roads and these cameras are used to capture images to analyze traffic density. Then the traffic signals are decided according to the density of traffic. Our technique can be effective to combat traffic on Indian Roads. A lot of time can be saved by deploying this system and also it conserves a lot of resources as well as the economy


Author(s):  
G. Kalyan

Traffic congestion is now a big issue. Although it seems to penetrate throughout the world, urban towns are the ones which are most effected. And it is expanding in nature that it is necessary to understand the density of roads in real time to better regulate signals and efficient management of transport. Various traffic congestions, such as limited capacity, unrestricted demand, huge Red Light waits might occur. While insufficient capacity and unlimited demand are somehow interconnected, their delay in lighting is difficult to encode and not traffic dependant. The necessity to simulate and optimise traffic controls therefore arises in order to better meet this growing demand. The traffic management of information, ramp metering, and updates in real-time has been frequently used in recent years for image processing and monitoring systems. An image processing can also be used for the traffic density estimation. This research describes the approach for the computation of real-time traffic density by image processing for using live picture feed from cameras. It focuses also on the algorithm for the transmission of traffic signals on the road according to the density of vehicles and therefore aims to reduce road congestion, which reduces the number of accidents.


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