The Mellin central projection transform

Authors

  • Jianwei Yang Nanjing University of Information Science and Technology http://orcid.org/0000-0002-2022-6002
  • Liang Zhang Nanjing University of Information Science and Technology
  • Zhengda Lu Nanjing University of Information Science and Technology

DOI:

https://doi.org/10.21914/anziamj.v58i0.10980

Keywords:

Mellin central projection transform, Mellin transform, affine invariants, feature extraction

Abstract

The central projection transform can be employed to extract invariant features by combining contour-based and region-based methods. However, the central projection transform only considers the accumulation of the pixels along the radial direction. Consequently, information along the radial direction is inevitably lost. In this paper, we propose the Mellin central projection transform to extract affine invariant features. The radial factor introduced by the Mellin transform, makes up for the loss of information along the radial direction by the central projection transform. The Mellin central projection transform can convert any object into a closed curve as a central projection transform, so the central projection transform is only a special case of the Mellin central projection transform. We prove that closed curves extracted from the original image and the affine transformed image by the Mellin central projection transform satisfy the same affine transform relationship. A method is provided for the extraction of affine invariants by employing the area of closed curves derived by the Mellin central projection transform. Experiments have been conducted on some printed Chinese characters and the results establish the invariance and robustness of the extracted features. doi:10.1017/S1446181116000341

Author Biographies

Jianwei Yang, Nanjing University of Information Science and Technology

School of Mathematics and Statistics

Liang Zhang, Nanjing University of Information Science and Technology

School of Mathematics and Statistics

Zhengda Lu, Nanjing University of Information Science and Technology

School of Mathematics and Statistics

Published

2017-07-20

Issue

Section

ANZIAM-ZPAMS Joint Meeting