| Title: | A passive optical location with limited range |
| Authors: | Jirků, Tomáš Fiala, Pavel Drexler, Petr |
| Citation: | AMTEE ’07 : seventh international conference on Advanced Methods in the Theory of Electrical Engineering : September 10-12, 2007 [Pilsen, Czech Republic]. |
| Issue Date: | 2007 |
| Publisher: | University of West Bohemia |
| Document type: | konferenční příspěvek conferenceObject |
| URI: | http://amtee.zcu.cz/AMTEE/ArchivedProceedings/proceedings_AMTEE_2007/data/section_i.html http://hdl.handle.net/11025/25804 |
| ISBN: | 978-80-7043-564-9 |
| Keywords: | pasivní optika;plazma;stochastické funkce;sekvence obrázků;funkce pravděpodobnosti |
| Keywords in different language: | passive optics;plasma;stochastic functions;picture sequence;probability function |
| Abstract in different language: | We know active and passive methods of a location. This article deals only with the passive location of dynamic targets (see [1]-[7]). The passive optics location is suitable just for the tracking of targets with mean velocity which is limited by the hardware basis. The aim of this work is to recognize plasma, particles etc. It is possible to propose such kind of evaluation methods which improve the capture probability markedly. The suggested method deals with the short-distance evaluation of targets. We suppose the application of three independent principles of how to recognize an object in a scanned picture. These principles use similar stochastic functions in order to evaluate an object location by means of simple mathematical operations. The methods are based on direct evaluation of picture sequence with the help of the histogram and frequency spectrum. We are trying to find out the probability of appearance of moving object in pictures. If the probability reaches a setting value, we will get a signal. The processing of dynamic pictures and their filtration represent a significant part of work [8]-[14]. Static objects, background (trees, buildings) must be filtered off before searching the objects. This filtration is also done by means of the probability function. The probability distribution of an object position is gained from a sequence of more pictures. |
| Rights: | © University of West Bohemia |
| Appears in Collections: | CPEE – AMTEE 2007 CPEE – AMTEE 2007 |
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