Detection and Recognition of Multi-language Traffic Sign Context by Intelligent Driver Assistance Systems
نویسندگان
چکیده مقاله:
Design of a new intelligent driver assistance system based on traffic sign detection with Persian context is concerned in this paper. The primary aim of this system is to increase the precision of drivers in choosing their path with regard to traffic signs. To achieve this goal, a new framework that implements fuzzy logic was used to detect traffic signs in videos captured along a highway from a vehicle. Implementing fuzzy logic in smart systems increases its inference and intelligent capabilities that results in better decision making in real-time conditions. In order to detect road sign’s texts, the combination of Canny Edge Detector Algorithms and Maximally Stable Extremal Regions (MSER) is used. Regions of an image that vary in properties, such as color or brightness, with respect to surrounding regions, are detected with the help of MSER algorithm. By using a multi-stage algorithm, Canny edge detector detects a wide range of edges in the acquired images. In order to join the individual characters for the final stage of detection of texts in traffic signs, a morphological mask operator is used. Finally, the recognition of the detected texts is carried out by employing MATLAB Optical Character Recognition (OCR). The overall accuracy of this new framework in detecting and recognizing texts is 90.6%.
منابع مشابه
Design an Intelligent Driver Assistance System Based On Traffic Sign Detection with Persian Context
In recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. Detection of traffic signs is an effective method to reach the mentioned aims. In this paper a new intelligent driver assistance system based on traffic...
متن کاملdesign an intelligent driver assistance system based on traffic sign detection with persian context
in recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. detection of traffic signs is an effective method to reach the mentioned aims. in this paper a new intelligent driver assistance system based on traffic sig...
متن کاملFPGA-Based Traffic Sign Recognition for Advanced Driver Assistance Systems
This paper presents the implementation of an embedded automotive system that detects and recognizes traffic signs within a video stream. In addition, it discusses the recent advances in driver assistance technologies and highlights the safety motivations for smart in-car embedded systems. An algorithm is presented that processes RGB image data, extracts relevant pixels, filters the image, label...
متن کاملTraffic Sign Recognition for Intelligent Vehicle/Driver Assistance System Using Neural Network on OpenCV
Traffic Sign Recognition (TSR) is used to regulate traffic signs, warn a driver, and command or prohibit certain actions. A fast real-time and robust automatic traffic sign detection and recognition can support and disburden the driver and significantly increase driving safety and comfort. Automatic recognition of traffic signs is also important for automated intelligent driving vehicle or driv...
متن کاملIntelligent Driver Assistance Systems
Over the past decade, the automotive industry has made many efforts to improve the comfort and first and foremost the safety of passenger cars. So-called driver assistance systems have been developed, which support the driver in his task of controlling (steering, breaking ...) a vehicle. Present-day assistance systems are entrusted with complex driving manoeuvres and are expected to operate cor...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ذخیره در منابع من قبلا به منابع من ذحیره شده{@ msg_add @}
عنوان ژورنال
دوره 20 شماره 2
صفحات 125- 136
تاریخ انتشار 2019-09-15
با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023