Improved spin images for 3D surface matching using signed angles

Publication Type

Conference Proceeding Article

Publication Date

10-2012

Abstract

Despite the popularity of spin images in surface matching and registration, disadvantages such as noise sensitivity and low discriminative ability still hindered their usefulness in real applications. In this paper, a novel approach was proposed for improving the spin images. The proposed method modified the standard spin images by using angle information between the normals of reference point and neighboring points. This information largely increased the robustness to noise without losing the intrinsic advantages of spin images. Moreover, signs were defined to incorporate the directions of angles which were shown to be able to further improve the descriptive power. Experiments were also conducted to show the outperformance of improved spin images under different levels of noise, and good agreements were obtained by comparing with the standard spin images and a recent popular 3D descriptor.

Keywords

Silicon, Noise, Shape, Standards, Clutter, Histograms, Robustness

Discipline

Artificial Intelligence and Robotics | Graphics and Human Computer Interfaces

Research Areas

Information Systems and Management

Publication

Proceedings of the 2012 19th IEEE International Conference on Image Processing, Orlando, Florida, USA, September 30 - October 3

First Page

537

Last Page

540

ISBN

9781467325349

Identifier

10.1109/icip.2012.6466915

Publisher

IEEE

City or Country

Orlando, FL, USA

Additional URL

https://doi.org/10.1109/icip.2012.6466915

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