Feature matching method study for uncorrected fish-eye lens image

Baofeng Zhang; Yanhui Jia; Juha Röning; Weijia Feng

doi:10.1117/12.2083009

8 February 2015 Feature matching method study for uncorrected fish-eye lens image

Baofeng Zhang, Yanhui Jia, Juha Röning, Weijia Feng

Proceedings Volume 9406, Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques; 94060C (2015) https://doi.org/10.1117/12.2083009
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

Because of the further from the center of image the lower resolution and the severe non-linear distortion are the characteristics of uncorrected fish-eye lens image, the traditional feature matching method can’t achieve good performance in the applications of fish-eye lens, which correct distortion firstly and then matches the features in image. Center-symmetric Local Binary Pattern (CS-LBP) is a kind of descriptor based on grayscale information from neighborhood, which has high ability of grayscale invariance and rotation invariance. In this paper, CS-LBP will be combined with Scale Invariant Feature Transform (SIFT) to solve the problem of feature point matching on uncorrected fish-eye image. We first extract the interest points in the pair of fish-eye images by SIFT, and then describe the corresponding regions of the interest points through CS-LBP. Finally the similarity of the regions will be evaluated using the chi-square distance to get the only pair of points. For the specified interest point, the corresponding point in another image can be found out. The experimental results show that the proposed method achieves a satisfying matching performance in uncorrected fish-eye lens image. The study of this article will be useful to enhance the applications of fish-eye lens in the field of 3D reconstruction and panorama restoration.

Citation Download Citation

Baofeng Zhang, Yanhui Jia, Juha Röning, and Weijia Feng "Feature matching method study for uncorrected fish-eye lens image", Proc. SPIE 9406, Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques, 94060C (8 February 2015); https://doi.org/10.1117/12.2083009

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Distortion

Image processing

3D modeling

Binary data

Detection and tracking algorithms

Panoramic photography

Image resolution

Show All Keywords

Keywords/Phrases

Search In:

Publication Years