Design and Implementation of Car Safety Device based on Computer Vision Technique

Abstract

In recent years due to the progress of embedded computer sensor and network the automotive electronic market starts to be considered as a blue ocean market More and more applications about automotive electronic that such as TPMS driving records pre-crash system AVM and self-driving car were developed and since the smart phone market reached saturation corporations eager to find out more ways to make profit they gradually begin investing more resource in this market However the security is most important part of automotive electronic and that is why “safety device” becomes one of the key directions in research field This thesis mainly aims to avoid accident that caused by driver or passenger who forget to check if any motorcycle or bicycle roared was passing by or getting near to them while getting off The classifier of this thesis was trained by Haar features with adaptive boosting and further filter the wrong target via Lucas-Kanade optical flow algorithm Finally it was implemented through embedded system In order to consider the computing rate (for Real Time) choose “Raspberry Pi2” to implement because this embedded computer has 900Mhz CPU clock and GPU In addition the program was developed via OpenCV library This thesis will carefully explain theory about computer algorithms that are used through comprehending those theories and probable situations in reality It could be easier to develop better methods for “motorcycle recognition” In the end this thesis will count out the correct rate and false alarm rate in the meantime problems will be concluded

Date of Award	2016 Jul 19
Original language	English
Supervisor	Teh-Lu Liao (Supervisor)