A New Approach for Skew Correction of Documents Based on Particle Swarm Optimization

Authors:
Javad Sadri;Mohamed Cheriet
Affiliations:
-;-
Venue:
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Year:
2009

Citing 0
Cited 2

Adaptive thresholding algorithm: Efficient computation technique based on intelligent block detection for degraded document images

Pattern Recognition
Document image analysis: issues, comparison of methods and remaining problems

Artificial Intelligence Review

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a novel approach for skew correction of documents. Skew correction is modeled as an optimization problem, and for the first time, Particle Swarm Optimization (PSO) is used to solve skew optimization. Anew objective function based on local minima and maxima of projection profiles is defined, and PSO is utilized to find the best angle that maximizes differences between values of local minima and maxima. In our approach, local minima and maxima converge to the locations of lines and spaces between lines. Results of our skew correction algorithm are shown on documents written in different scripts such as Latin and Arabic related scripts (e.g. Arabic, Farsi,Urdu,...). Experiments show that our algorithm can handle a wide range of skew angles, also it is robust to gray level and binary images of different scripts.