Adaptive Radial Projection on Fourier Magnitude Spectrum for Document Image Skew Estimation

TL;DR

This paper introduces a novel Fourier-based skew estimation method using adaptive radial projection, demonstrating superior robustness and accuracy on a new dataset, with comprehensive analysis of improvements over existing techniques.

Contribution

The paper proposes a new adaptive radial projection technique for Fourier magnitude spectrum to improve document image skew estimation accuracy.

Findings

Outperforms existing skew estimation methods

Robust and reliable across diverse document images

Provides a new high-quality dataset DISE-2021

Abstract

Skew estimation is one of the vital tasks in document processing systems, especially for scanned document images, because its performance impacts subsequent steps directly. Over the years, an enormous number of researches focus on this challenging problem in the rise of digitization age. In this research, we first propose a novel skew estimation method that extracts the dominant skew angle of the given document image by applying an Adaptive Radial Projection on the 2D Discrete Fourier Magnitude spectrum. Second, we introduce a high quality skew estimation dataset DISE-2021 to assess the performance of different estimators. Finally, we provide comprehensive analyses that focus on multiple improvement aspects of Fourier-based methods. Our results show that the proposed method is robust, reliable, and outperforms all compared methods. The source code is available at https://github.com/phamquiluan/jdeskew.