An Electronic Image Stabilization Algorithm for Vision System of Intelligent Vehicles

doi:10.11908/j.issn.0253-374x.21491

Home > Archive>Volume 50, Issue 4, 2022 >497-503. DOI:10.11908/j.issn.0253-374x.21491

An Electronic Image Stabilization Algorithm for Vision System of Intelligent Vehicles
DOI:
                        10.11908/j.issn.0253-374x.21491
                    
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                        ZHANG Ning1ZHANG Ning
School of Mechanical Engineering， Southeast University， Nanjing 211189， China
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ZHANG Haobin1ZHANG Haobin
School of Mechanical Engineering， Southeast University， Nanjing 211189， China
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WU Jianhua1WU Jianhua
School of Mechanical Engineering， Southeast University， Nanjing 211189， China
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YANG Yuan2YANG Yuan
School of Instrument Science and Engineering， Southeast University， Nanjing 210096， China
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YIN Guodong1YIN Guodong
School of Mechanical Engineering， Southeast University， Nanjing 211189， China
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Affiliation:1.School of Mechanical Engineering， Southeast University， Nanjing 211189， China;2.School of Instrument Science and Engineering， Southeast University， Nanjing 210096， China
Clc Number:U461.4
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Abstract:

Vehicular camera is an essential part of the vision system of intelligent vehicles. In harsh road or extreme conditions， due to the significant vibration of vehicles， the image sequence collected by the vehicular camera vibrates. Aimed at this problem， an electronic image stabilization algorithm for vehicle vision system is proposed. Considering the real-time requirements under vehicle conditions， the ORB algorithm （oriented fast and rotated BRIEF） is selected for feature detection and description. In order to improve the accuracy of matching and the efficiency of feature points， the traditional random sampling consistency algorithm is improved to enhance its adaptability to multiple and centralized matching points. The classical Kalman filter is sensitive to the initial value. Therefore， to adapt to the extreme conditions， the adaptive Kalman filter is used. Finally， a gasoline model vehicle with significant vibration characteristics is established， and experiments are conducted under harsh road conditions. The correctness and effectiveness of the proposed electronic image stabilization algorithm are verified under conditions more extreme than normal.

Key words:electronic image stabilization;vision system;intelligent vehicles;adaptive Kalman filter;gasoline model car

Reference

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ZHANG Ning, ZHANG Haobin, WU Jianhua, YANG Yuan, YIN Guodong. An Electronic Image Stabilization Algorithm for Vision System of Intelligent Vehicles[J].同济大学学报(自然科学版),2022,50(4):497~503

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Received:October 18,2021
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Online: May 06,2022
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