Automatic image registration based on convexity model and full-scale image segmentation

Kaimin Sun; Haigang Sui; Yan Chen

doi:10.1117/12.750006

15 November 2007 Automatic image registration based on convexity model and full-scale image segmentation

Kaimin Sun, Haigang Sui, Yan Chen

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67863A (2007) https://doi.org/10.1117/12.750006
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Kaimin Sun, Haigang Sui, and Yan Chen "Automatic image registration based on convexity model and full-scale image segmentation", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67863A (15 November 2007); https://doi.org/10.1117/12.750006

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