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Volume 31, Issue 2
A Fast Classification Method for Single-Particle Projections with a Translation and Rotation Invariant

Xia Wang & Guoliang Xu

DOI: 10.4208/jcm.1212-m4128

J. Comp. Math., 31 (2013), pp. 137-153.

Published online: 2013-04

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  • Abstract

The aim of the electron microscopy image classification is to categorize the projection images into different classes according to their similarities. Distinguishing images usually requires that these images are aligned first. However, alignment of images is a difficult task for a highly noisy data set. In this paper, we propose a translation and rotation invariant based on the Fourier transform for avoiding alignment. A novel classification method is therefore established. To accelerate the classification speed, secondary-classes are introduced in the classification process. The test results also show that our method is very efficient and effective. Classification results using our invariant are also compared with the results using other existing invariants, showing that our invariant leads to much better results.

  • Keywords

Classification, Fourier transform, Translation and rotation invariant, Secondary-class.

  • AMS Subject Headings

65D17.

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{JCM-31-137, author = {Xia Wang and Guoliang Xu}, title = {A Fast Classification Method for Single-Particle Projections with a Translation and Rotation Invariant}, journal = {Journal of Computational Mathematics}, year = {2013}, volume = {31}, number = {2}, pages = {137--153}, abstract = {

The aim of the electron microscopy image classification is to categorize the projection images into different classes according to their similarities. Distinguishing images usually requires that these images are aligned first. However, alignment of images is a difficult task for a highly noisy data set. In this paper, we propose a translation and rotation invariant based on the Fourier transform for avoiding alignment. A novel classification method is therefore established. To accelerate the classification speed, secondary-classes are introduced in the classification process. The test results also show that our method is very efficient and effective. Classification results using our invariant are also compared with the results using other existing invariants, showing that our invariant leads to much better results.

}, issn = {1991-7139}, doi = {https://doi.org/10.4208/jcm.1212-m4128}, url = {http://global-sci.org/intro/article_detail/jcm/9726.html} }
TY - JOUR T1 - A Fast Classification Method for Single-Particle Projections with a Translation and Rotation Invariant AU - Xia Wang & Guoliang Xu JO - Journal of Computational Mathematics VL - 2 SP - 137 EP - 153 PY - 2013 DA - 2013/04 SN - 31 DO - http://doi.org/10.4208/jcm.1212-m4128 UR - https://global-sci.org/intro/article_detail/jcm/9726.html KW - Classification, Fourier transform, Translation and rotation invariant, Secondary-class. AB -

The aim of the electron microscopy image classification is to categorize the projection images into different classes according to their similarities. Distinguishing images usually requires that these images are aligned first. However, alignment of images is a difficult task for a highly noisy data set. In this paper, we propose a translation and rotation invariant based on the Fourier transform for avoiding alignment. A novel classification method is therefore established. To accelerate the classification speed, secondary-classes are introduced in the classification process. The test results also show that our method is very efficient and effective. Classification results using our invariant are also compared with the results using other existing invariants, showing that our invariant leads to much better results.

Xia Wang and Guoliang Xu. (2013). A Fast Classification Method for Single-Particle Projections with a Translation and Rotation Invariant. Journal of Computational Mathematics. 31 (2). 137-153. doi:10.4208/jcm.1212-m4128
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