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Zaznava prevožene rdeče luči na podlagi algoritmov računalniškega vida
ID ŠUŠTERIČ, MIHA (Author), ID Perš, Janez (Mentor) More about this mentor... This link opens in a new window

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PID: 20.500.12556/rul/0a0f372d-eca2-4f4a-8ae2-524dba19b369

Abstract
Raziskave s področja cestne varnosti so pokazale, da je mogoče število prekrškov vožnje skozi rdečo luč in posledično prometne nesreče, katerim botruje tovrsten prekršek, znatno zmanjšati, s postavitvijo sistemov za samostojno zaznavo prekrškarjev. Osrednja tema tega dela je prometen nadzorni sistem na osnovi računalniškega vida, ki zazna spremembo semaforja brez signala semaforskega krmilnika ter zazna prevoženo rdečo luč. Ob takšnem dogodku sistem samodejno posname in shrani prekršek. Poudarek je na kompaktnosti in preprosti postavitvi sistema, saj je to nadgradnja obstoječih rešitev, ki so se izkazale za nepraktične ravno zaradi kompleksnosti vgradnje. Sistemska rešitev je pripravljena z nadzorno kamero Axis P1357 in mikroračunalnikom Raspberry Pi 2, v programskem jeziku Python z uporabo knjižnice OpenCV. V okviru naloge sem opisali izzive, s katerimi sem se soočal pri programiranju in rešitve, ki sem jih pripravil, ter podal mnenje, kaj in kako bi se dalo izboljšati. Vodilo naloge je bilo pripraviti rešitev za nadzor prometa z opremo, ki je bila dostopna v laboratoriju.

Language:Slovenian
Keywords:cestna varnost, prometni nadzor, računalniški vid, semafor
Work type:Master's thesis/paper
Organization:FE - Faculty of Electrical Engineering
Year:2016
PID:20.500.12556/RUL-87763 This link opens in a new window
Publication date in RUL:13.12.2016
Views:2098
Downloads:418
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Secondary language

Language:English
Title:Detecting Red Light Runs Using Computer Vision Algorithms
Abstract:
Researchers have shown, that the rate of traffic lights violations and thus related accidents can be significantly reduced by introducing autonomous red-light cameras to crossroads. The main topic of this work, is autonomous traffic control system for intersections, based on computer vision, that can detect change in traffic lights, without any signals from traffic lights controller and can identify a red light runner. That triggers the system to record and save the footage of the event for later inspection. Emphases of the project is to create a compact, easy to install system, that upgrades on the now existing systems, that need modifications of road surfaces and traffic lights controllers. Solution is made with a common security camera AXIS P1357 and microcomputer Raspberry Pi 2, in Python whit the use of OpenCV library. As a part of this work I discuss challenges and solutions, to the problems I encountered and I give a few suggestions as to what could be done better. The main thread of this work was to create a solution for traffic control with the equipment found in the laboratory.

Keywords:road safety, traffic control, computer vision, traffic lights

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