Traffic Sign Detection through Image Processing and Pattern Recognition
Loading...
Date
2013
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Faculty of Engineering and Natural Science
Abstract
Urbanisation, growth of cities and their population bring serious changes into our lives. That includes increasing numbers of cars on the road and traffic complexity. Since the very early stages of car and traffic development the very first concern of the designers and engineers was safety on the road. Most commonly it depends on the drivers and pedestrians directly. Attentiveness or inattentiveness of the traffic participants is one of the reasons why accidents can happen. Traffic signs provide important information for drivers about road condition and hazards. Their discriminating shape and colors make them easily recognizable by humans. Same factors can help development of a visionbased TSR system. Beside the application of TSR in autonomous vehicles, it can also serve as an assistant driver (e.g. when combined with speedometer output) to notify the driver about approaching a traffic sign (e.g. even before driver sees it) or his risky behavior (like driving above the speed limit). Safe driving was one of the three identified main work areas and meant to employ autonomous vehicle control for safer driving with less mental load on the driver. My proposed method is composed of three main Stages: 1. detection, which is performed using a novel application of maximally stable extremal regions 2. recognition, which is performed with LBP features 3. mobility, which is performed using mobile phone
Description
Keywords
Citation
Zhanibekov D / Traffic Sign Detection through Image Processing and Pattern Recognition / 2013 / 6M070400— «Computing systems and software»