An Effective Approach for Noise Robust and Rotation Invariant Handwritten Character Recognition Using Zernike Moments Features and Optimal Similarity Measure-Reference-Cited by-同舟云学术

An Effective Approach for Noise Robust and Rotation Invariant Handwritten Character Recognition Using Zernike Moments Features and Optimal Similarity Measure

Published:2020-08-17 Issue:13 Volume:34 Page:1011-1037
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Singh Chandan¹,Aggarwal Ashutosh¹²

Affiliation:

1. Department of Computer Science, Punjabi University, Patiala, India

2. Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2020.1796370

Reference24 articles.

1. Orthogonal moment features for use with parametric and non-parametric classifiers

2. On the circle polynomials of Zernike and related orthogonal sets

3. Fast Zernike wavelet moments for Farsi character recognition

4. A Zernike Moment Phase-Based Descriptor for Local Image Representation and Matching

5. Errata and comments on “Generic orthogonal moments: Jacobi–Fourier moments for invariant image description”

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