Vehicle and Weather Detection Using Real Time Image Processing Using Optical Flow and Color Histogram

被引:0
作者
Padilla, Dionis A. [1 ]
Villaverde, Jocelyn F. [1 ]
Magdaraog, Jason Jovin T. [2 ]
Oconer, Andrew Justin L. [2 ]
Ranjo, Juan Paulo [2 ]
机构
[1] Mapua Univ, Sch Elect Elect & Comp Engn, Manila, Philippines
[2] Mapua Univ, Manila, Philippines
来源
CONFERENCE PROCEEDINGS OF 2019 5TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND ROBOTICS (ICCAR) | 2019年
关键词
component; Image Processing; Gaussian Mixture Model; Foreground Detector; Blob Analysis;
D O I
10.1109/iccar.2019.8813346
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Image processing is the method that will be used in this system. A surveillance camera will be mounted at an optimal position so that it could detect the vehicles efficiently. The Foreground Detector and Blob Analysis make up the techniques that will be used to identify an object as a vehicle in a video sequence. The Mixture Model, specifically Gaussian must have an initialized Foreground Detector that has sampled a video frame before it can be used. After initializing Foreground Detector, Blob Analysis would be used to detect vehicles and place bounding box. Image processing used in detecting vehicles is used in determining the weather condition. The only difference is that histogram would also be used. Since it will operate in real-time, it is capable of detecting the density of vehicles on the lane even in various conditions like raining or changes in illumination.
引用
收藏
页码:880 / 883
页数:4
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