Open AccessAI Enabled Blind Spot Detection using Rcnn Based Image Processing
Author(s) -
Amir Vahid,
Dastjerdi,
Rajkumar Buyya,
Aref Meddeb,
Constantinos Kolias,
Angelos Stavrou,
Irena Bojanova,
Richard Kuhn,
Dusit Niyato,
Thai Dinh,
Hoang,
Cong Nguyen,
Ping Luong,
Dong Wang,
In Kim,
Zhu Han,
David Park,
Daqiang Zhang,
Laurence Yang,
Min Chen,
Shengjie Zhao,
Minyi Guo,
Yin Zhang,
David Metcalf,
T Sharlin,
Melinda Milliard,
Michael Gomez,
Schwartz,
Glenn Parsons,
Guiou Kobayashi,
Maria,
Eunice Quilici-Gonzalez,
Mariana,
Claudia Broens,
Jos,
Artur Quilici-Gonzalez,
Huadong Ma,
Liang Liu,
Anfu Zhou,
Dong Zhao,
Huadong Ma,
Liang Liu,
Anfu Zhou,
Dong Zhao,
Jonathan Margulies,
Keshav Sood,
Shui Yu,
Yong Xiang,
Michele Nitti,
Virginia Pilloni,
Giuseppe Colistra,
Luigi Atzori,
Mohammad Abdur Razzaque,
Marija Milojevic-Jevric,
Andrei Palade,
Siobhn Clarke,
Maria Rita Palattella,
Mischa Dohler,
Alfredo Grieco,
Mohamed Essaid Khanouche,
Yacine Amirat,
Abdelghani Chibani,
Moussa Kerkar,
Ali Yachir,
Oladayo Bello,
Sherali Zeadally,
Phillip Laplante,
Nancy Laplante,
Pawani Porambage,
Mika Ylianttila,
Corinna Schmitt,
Pardeep Kumar,
Andrei Gurtov,
Athanasios Vasilakos,
Phillip Laplante,
Jefrey Voas,
Nancy Laplante,
Sara Amendola,
Rossella Lodato,
Sabina Manzari,
Cecilia Occhiuzzi,
Gaetano Marrocco,
Yi Xu,
Abdelsalam Helal,
Yunchuan Sun,
Houbing Song,
Antonio Jara,
Rongfang Bie,
Yuvraj Agarwal,
Anind Dey,
Zhangbing Zhou,
Beibei Yao,
Riliang Xing,
Lei Shu,
Shengrong Bu,
S Raja,
T Rajkumar,
Vivek Pandiya,
Raj,
S Raja,
T Sampradeepraj,
M Rajesh,
J Gnanasekar,
M Rajesh,
J Gnanasekar,
M Rajesh,
M Rajesh,
M Rajesh,
M Rajesh,
K Balasubramaniaswamy,
S Aravindh
Publication year - 2019
Publication title -
international journal of recent technology and engineering (ijrte)
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1006.0782s519
Subject(s) - blind spot , computer vision , cruise control , artificial intelligence , computer science , key (lock) , motion detection , motion (physics) , control (management) , computer security
Due to the rapid increase in the rate of road accidents and traffic density, modern automobiles are equipped with intelligent systems like Adaptive cruise control and Lane Departure Warning System. Therear-view mirror can be effective to observe a limited range only and there are zones that cannot be viewed. This region is referred to as the blind spot. Therefore, we present a method to detect the vehicles from the side and the rear for Blind Spot Detection with vision system incorporating RCNN. Blind spot detection is a key technology among driver aids that provides 360 degrees of electronic coverage around the car during motion.The methodology presented in this paper uses two stereo cameras as input devices which constantly capture the images at the blind spot area and the information is passed to the main controlling unit. Potholes are also detected and the alert is sent to the nearby vehicle. The incorporation of Artificial Intelligence would help in enhancing the picture quality and blur or cancel the background images probable of misreading the target image. RCNN is used for the vehicle detection and for evaluating the relative distance between the vehicles.This technology allows us to provide a realistic environment for commercial vehicle drivers as they can’t monitor the side and rear-view mirrors all the time, making the whole driving experience more comfortable
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