A Novel Approach to Skew-Detection and Correction of English Alphabets for OCR

TL;DR

This paper introduces a simple, efficient method for detecting and correcting skew in English alphabet images to improve OCR accuracy, using a novel COG-based detection and sub-pixel shifting correction.

Contribution

It presents a new skew-detection algorithm based on the Centre of Gravity method and a correction technique using sub-pixel shifting, optimized for OCR preprocessing.

Findings

The proposed algorithm effectively detects skew in alphabet images.

The correction method improves OCR accuracy by aligning characters properly.

Performance analysis shows the method is efficient and reliable.

Abstract

Optical Character Recognition has been a challenging field in the advent of digital computers. It is needed where information is to be readable both to humans and machines. The process of OCR is composed of a set of pre and post processing steps that decide the level of accuracy of recognition. This paper deals with one of the pre-processing steps involved in the OCR process i.e. Skew (Slant) Detection and Correction. The proposed algorithm implemented for skew-detection is termed as the COG (Centre of Gravity) method and for that of skew-correction is Sub-Pixel Shifting method. The algorithm has been kept simple and optimized for efficient skew-detection and correction. The performance analysis of the algorithm after testing has been aptly demonstrated.