Share Email Print

Proceedings Paper

Automatic image registration based on convexity model and full-scale image segmentation
Author(s): Kaimin Sun; Haigang Sui; Yan Chen
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Image registration plays a critically important role in many practical problems in diverse fields. A new object-oriented image matching algorithm is presented based on the convexity model (CM) and full-scale image segmentation. The core idea of this matching algorithm is to use image objects as matching unit rather than points or lines. This algorithm firstly converts images into image objects trees by full-scale segmentation and convexity model restriction. Because image objects which accord with the convexity model have rich and reliable statistical information and stable shapes, more characteristics can be used in object-based image matching than pixel-based image matching. Initial experiments show that matching algorithm proposed in this paper is not sensitive to rotation and resolution distortion, which can accomplish the image matching and registration automatically.

Paper Details

Date Published: 15 November 2007
PDF: 9 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67863A (15 November 2007); doi: 10.1117/12.750006
Show Author Affiliations
Kaimin Sun, Wuhan Univ. (China)
Haigang Sui, Wuhan Univ. (China)
Yan Chen, Wuhan Univ. (China)

Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition
Tianxu Zhang; Tianxu Zhang; Carl Anthony Nardell; Carl Anthony Nardell; Hanqing Lu; Duane D. Smith; Hangqing Lu, Editor(s)

© SPIE. Terms of Use
Back to Top