Title :
Automatic Position Registration of Street-level Fisheye Images into Aerial Image Using Line Structures and Mutual Information
Author :
Zouqi, Mehrnaz ; Samarabandu, Jagath ; Zhou, Yanbo
Author_Institution :
Image Recognition & Intell. Syst. Lab., Univ. of Western Ontario, London, ON, Canada
fDate :
May 31 2010-June 2 2010
Abstract :
Geospatial imaging is a relatively new term which is increasingly becoming more important for both government and commercial sectors. Images taken at street level can be geo-coded using a camera equipped with a built-in GPS device. However, the location that GPS provides are prone to errors up to 10 meters. In this paper we propose an algorithm to find the accurate location of a street-level image taken with a fisheye camera within a satellite image. Our algorithm is based on straight line detection and matching using Hough transform and gradient information around the detected lines. The rotation parameter is obtained using the best corresponding lines. Then mutual information (MI) is used as the similarity measure along the best match lines to determine the translational parameters. Moreover, as the correction process is carried out for a consecutive series of images rather than an individual image, the final location of each image will be assessed to be consistent with its neighboring images.
Keywords :
Global Positioning System; Hough transforms; cameras; geophysical image processing; Hough transform; aerial image; automatic position registration; built in GPS device; fisheye camera; geospatial imaging; line structures; mutual information; satellite image; street level fisheye images; Mutual information; line matching; multi-modal image registration; mutual information;
Conference_Titel :
Computer and Robot Vision (CRV), 2010 Canadian Conference on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4244-6963-5
DOI :
10.1109/CRV.2010.22