A Novel Approach to Skew-Detection and Correction of English Alphabets for OCR
This addresses a pre-processing step in OCR to improve accuracy, but it is incremental as it builds on existing methods.
The paper tackles skew detection and correction in OCR by proposing a COG method for detection and Sub-Pixel Shifting for correction, achieving efficient performance as demonstrated in tests.
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.