BibTex Citation Data :
@article{YPJ17105, author = {Laila Rahmawati and Kusworo Adi}, title = {Rancang bangun penghitung dan pengidentifikasi kendaraan menggunakan Multiple Object Tracking}, journal = {Youngster Physics Journal}, volume = {6}, number = {1}, year = {2017}, keywords = {Counters and vehicle identifiers, multiple object tracking, Gaussian mixture models, Kalman Filter}, abstract = { Detection of a vehicle with a video camera is one accurate technology for detecting vehicles efficiently and can be used for large-scale data collection. This study has been conducted implementation of counters and identifiers vehicles on the highway using multiple object tracking. The system uses an algorithm Gaussian mixture models and Kalman filter to detect and track the position, speed, direction of motion and size of vehicles from time to time in each image frame. The process of counting and identifying the vehicle consists of several stages of image acquisition, object detection using a Gaussian mixture models, morphology, object tracking using a Kalman filter and counting as well as the identification of the vehicle. The results of system performance is obtained by calculating the value of accuracy. Best performance results from the system counters and identifiers of vehicles on the highway using multiple object tracking obtained by the time of the morning and the worst at night. The results of the performance measurement system and vehicle identifiers using multiple object tracking accuracy of the results obtained on the morning of 94%, by 90% during the day, in the afternoon by 85%, and the evenings of 59%. Keywords : Counters and vehicle identifiers, multiple object tracking, Gaussian mixture models, Kalman Filter }, issn = {2302-7371}, pages = {70--75} url = {https://ejournal3.undip.ac.id/index.php/bfd/article/view/17105} }
Refworks Citation Data :
Detection of a vehicle with a video camera is one accurate technology for detecting vehicles efficiently and can be used for large-scale data collection. This study has been conducted implementation of counters and identifiers vehicles on the highway using multiple object tracking. The system uses an algorithm Gaussian mixture models and Kalman filter to detect and track the position, speed, direction of motion and size of vehicles from time to time in each image frame. The process of counting and identifying the vehicle consists of several stages of image acquisition, object detection using a Gaussian mixture models, morphology, object tracking using a Kalman filter and counting as well as the identification of the vehicle. The results of system performance is obtained by calculating the value of accuracy. Best performance results from the system counters and identifiers of vehicles on the highway using multiple object tracking obtained by the time of the morning and the worst at night. The results of the performance measurement system and vehicle identifiers using multiple object tracking accuracy of the results obtained on the morning of 94%, by 90% during the day, in the afternoon by 85%, and the evenings of 59%.
Keywords: Counters and vehicle identifiers, multiple object tracking, Gaussian mixture models, Kalman Filter
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