An Electronic Image Stabilization Algorithm for Vision System of Intelligent Vehicles

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