Automatic traffic monitoring using satellite images

Abstract

Vital problems in transportation and safety of transportation, especially in hi ways, are considered as very important nowad monitoring aims at acquisition and analysis such as presence and numbers of vehicles driver warning systems developed mainly for safety purposes. In the past some methods hav for road and vehicle recognition, which eithe the results was not acceptable, or tolera achieved only in specific conditions. This artic approach for recognizing the vehicle and the high-resolution images in non-urban areas. O of this research was to control the traffic jam recognize the traffic density quickly and recognition, they used feature extraction, ima machine learning like Hough transform, thresholding operation for road detectio extraction and SVM for Vehicles' detection results is about 85 percent and it show procedure has the suitable efficiency.

Estimating online vacancies in real-time road traffic monitoring with traffic sensor data stream

“…Several studies [3,8] been published that have explored ways to overcome the limitations of coverage with traditional technologies by making a trade-off between precision and scalability. Some studies proposed using high-resolution satellite imagery to make up for coverage shortages [9][10][11]. However, the availability of the proposed approaches is limited by weather and other factors that impact the precision and timeliness of the data provided by these traditional technologies.…”

Affine-Function Transformation-Based Object Matching for Vehicle Detection from Unmanned Aerial Vehicle Imagery

“…Thus, due to the advantages of high convenience, low cost, and abundant information, remote sensing sensors and their resultant images have been applied to various traffic-related applications. Consequently, extensive studies have also been conducted for information extraction and interpretation from remote sensing images, such as road segmentation [3,4], road feature extraction [5,6], vehicle detection [7,8], and traffic monitoring [9,10].…”