In this paper a double source images fusion algorithm is presented. Its task is to enhance temperature feature of objects located on the scene. Presented solution is design to be executed in real-time environment. It consists of three stages: in the first part the differences between acquired double source images are examined in order to determine their intersection. Then for each analysed image the contours of all objects located on the scene are determined. This operation is essential to solve disparition issue. In the last stage, based on determined contours and their match coefficient the images are fused. The enhanced temperature feature is displayed on one image acquired from day-light camera.
Modern Intelligent Transport Systems incorporate the traffic control strategies that are based not only on long term traffic analysis and forecasts, but also on the real time events detection like accidents or high congestion. The flexibility of these systems depends on accurate and precise data set describing the current state of road network. To estimate it, the data from various sources like: video surveillance, induction loops or vehicles itself (Vehicle to Infrastructure communication -V2I) is gathered. Excluding detection errors, the video surveillance data is a reliable source of general information about the traffic flow. On the other hand, the vehicle communication can provide less reliable, but more detailed information about a particular vehicle like: its engine state or planned manoeuvre. Unreliable or forged C2I information can be used to disturb traffic or to gain a higher priority on the road. The paper reviews the fusion algorithms that are used to merge data from video tracking algorithms and vehicular networks. Based on the survey, a weighted fusion algorithm is proposed that estimates the acquired data reliability. The algorithm uses the video surveillance data as a filter for C2I communication. Finally, applications for microscopic traffic models and safety issues are taken into consideration.
3
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
Artykuł prezentuje algorytm przetwarzania sygnału temperatury bazujący na wykorzystaniu nieprecyzyjnych informacji o panujących warunkach pomiarowych, specyfice obiektu elektrotermicznego itp. Zastosowano zbiory rozmyte dla potrzeb reprezentacji wiedzy nieprecyzyjnej oraz algorytm konsolidacji danych.
EN
New approach to intelligent temperature signal processing has been proposed. The method is based on the use of imprecise information concerning the conditions under which the temperature readings have been obtained. The fuzzy sets have been applied for representation of imprecise knowledge and fusion algorithm of imprecise information and uncertain temperature readings has been proposed.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.