K-Algorithm A Modified Technique for Noise Removal in Handwritten Documents

TL;DR

This paper introduces K-Algorithm, a two-stage noise removal method for handwritten document images, improving OCR pre-processing by enhancing noise filtering and binarization over traditional median filtering.

Contribution

The paper presents a novel two-stage noise removal technique called K-Algorithm, specifically designed for handwritten document images, demonstrating improved results over existing median filtering methods.

Findings

K-Algorithm outperforms median filtering in noise removal.

Enhanced noise reduction improves OCR accuracy.

The method is effective for handwritten document pre-processing.

Abstract

OCR has been an active research area since last few decades. OCR performs the recognition of the text in the scanned document image and converts it into editable form. The OCR process can have several stages like pre-processing, segmentation, recognition and post processing. The pre-processing stage is a crucial stage for the success of OCR, which mainly deals with noise removal. In the present paper, a modified technique for noise removal named as K-Algorithm has been proposed, which has two stages as filtering and binarization. The proposed technique shows improvised results in comparison to median filtering technique.