Abstract
Problem statement: As vehicle population increases, Intelligent Transportation Systems (ITS) become more significant and mandatory in today’s overpopulated world. Vital problems in transportation such as mobility and safety of transportation are considered more, especially in metropolitans and highways. The main road traffic monitoring aims are: the acquisition and analysis of traffic figures, such as number of vehicles, incident detection and automatic driver warning systems are developed mainly for localization and safety purposes. Approach: The objective of this investigation was to propose a strategy for road extraction and incident detection using aerial images. Real time extraction and localization of roadways in an satellite image is an emerging research field which can applied to vision-based traffic controlling and unmanned air vehicles navigation. Results: The results of the proposed incident detection algorithm show that it has good detection performance, the maximum angle of vehicles applied for incidet detection is 45° and the performance for learning system in order to vehicle detection is 86%. This performance achived in testing algorithm on 45 highway aerial images. Conclusion: In order to consider with the high complexity of this kind of imagery, we integrate knowledge about roadways using formulated scale-dependent models. The intensity images are used for the extraction of road from satellite images. Threshold techniques, neural network and Radon transform are used for the road extraction, vehicle detection and incident detection. Results indicated that in most aerial images the incident can be detect by applying the angle algorithm.
Highlights
Traffic controlling and incident detection is an emerging research topic which is rapidly increasing interest in traffic controlling systems
Techniques based on morphology and neural network for vehicle detection and road extraction had developed in machine vision, but only a few researchers have investigated the detection of traffic sensing and incident detection on aerial images (Lairong et al, 2010)
The results shown that the alghorithm can detect the incident in most of the roadway images. this scheme, has some disadvantages: its performance is 80% and it cannot detect the vehicles outside the road
Summary
Traffic controlling and incident detection is an emerging research topic which is rapidly increasing interest in traffic controlling systems. With considering high-resolution aerial imageries, existence of an intelligence road extraction and vehicle detection system which is be able to control the road traffic has had more remarkable performance. Investigations about road extraction and vehicle detection in aerial imageries involved in information and data related to GIS and this maintained data needs to become up to date in every certain period of time. Road extraction and vehicle detection for incident detection in aerial imageries is a newly controversial issue in computer vision that has some influences many other projects and operations such as traffic controlling and incident detection in highways. Road and vehicle detection for incident detection, essential items and their characteristics and execution on aerial imageries, Sec. Results: The experiment results of proposed algorithm. Conclusion: A proposal about works for future on this topic
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