jdeskew 0.0.7

Document Image Skew Estimation using Adaptive Radial Projection

Document Image Skew Estimation

I. Installation

I.1. pip

pip install jdeskew

I.2. Docker

docker pull phamquiluan/jdeskew

II. How-to-use

II.1. using python

from jdeskew.estimator import get_angle
angle = get_angle(image)

from jdeskew.utility import rotate
output_image = rotate(image, angle)

II.2. using cog

cog build --debug
cog predict -i input=@skew.png

# Output:
# Running prediction...
# {
#   "angle": -0.12520868113522532
# }

Performance Comparison on DISE 2021

CE: Correct Estimation rate

WE: Worst Error

	AED	TOP80	CE	WE
FredsDeskew	10.82	0.09	0.54	109
PypiDeskew	16.59	0.24	0.2	141
Koo, Hyung Il et al.	0.22	0.09	0.48	9.43
CMC-MSU	0.27	0.11	0.43	23.2
LRDE-EPITA-a	0.14	0.06	0.66	10.61
Our (1024)	0.11	0.07	0.67	1.13
Our (1500)	0.09	0.05	0.78	1.13
Our (2048)	0.08	0.04	0.84	1.13
Our (3072)	0.07	0.04	0.86	1.13
Our (4096)	0.08	0.04	0.83	1.18

Citation

L. Pham, T. A. Tran, "Document Image Skew Estimation using Adaptive Radial Projection", 2022.

@misc{luandise2022,
  title={ADAPTIVE RADIAL PROJECTION ON FOURIER MAGNITUDE SPECTRUM FOR
DOCUMENT IMAGE SKEW ESTIMATION},
  author={Luan Pham, Hao Hoang, Toan Mai, and Tuan Anh Tran},
  url={https://github.com/phamquiluan/jdeskew},
  year={2022}
}