The jam flow condition is one of the main traffic states in traffic flow theory and the most difficult state for sectional traffic information acquisition. Since traffic information acquisition is the basis for the application of an intelligent transportation system, research on traffic vehicle counting methods for the jam flow conditions has been worthwhile. A low-cost and energy-efficient typ...

The network traffic data provided for the design of intrusion detection always are large with ineffective information and enclose limited and ambiguous information about users’ activities. We study the problems and propose a two phases approach in our intrusion detection design. In the first phase, we develop a correlation-based feature selection algorithm to remove the worthless information fr...

Rapid urban growth is resulting into increase in travel demand and private vehicle ownership in urban areas. In the present scenario the existing infrastructure has failed to match the demand that leads to traffic congestion, vehicular pollution and accidents. With traffic congestion augmentation on the road, delay of commuters has increased and reliability of road network has decreased. Four s...

We present an accurate and efficient system for traffic sign recognition in a real-world driving scene video. The proposed system uses local structure features to achieve high, illumination-invariant accuracy in detection and recognition. We exploit a property of traffic signs, namely, shared boundary shapes, to enhance the speed and accuracy of the detection step. A multi-level SVM structure i...

Automatic road extraction from aerial images can be very helpful in traffic control and vehicle guidance systems. Most of the road detection approaches are based on image segmentation algorithms. Color-based segmentation is very sensitive to light changes and consequently the change of weather condition affects the recognition rate of road detection systems. In order to reduce the light change ...

This paper presents a new scheme to implement an event-driven traffic ticketing system. The system consists of two modules, namely, (1) event detection module, (2) database management module to execute information retrieval and deliver traffic tickets. In this paper, the notable contribution is an automatic detection of traffic ticketing events from video footages and immediate notification of ...

A unified method for statistical anomaly detection in intrusion detection systems is theoretically introduced. It is based on estimating a dispersion measure of numerical or symbolic data on successive moving windows in time and finding the times when a relative change of the dispersion measure is significant. Appropriate dispersion measures, relative differences, moving windows, as well as tec...

Current network monitoring systems rely strongly on signature-based and supervised-learning-based detection methods to hunt out network attacks and anomalies. Despite being opposite in nature, both approaches share a common downside: they require the knowledge provided by an expert system, either in terms of anomaly signatures, or as normal-operation profiles. In a diametrically opposite perspe...