K-Algorithm A Modified Technique for Noise Removal in Handwritten Documents
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.
Code (0)
등록된 구현이 없습니다.
Tasks
BinarizationOptical Character Recognition (OCR)Similar Papers 제목 키워드 기반
Modified Segmentation Algorithm for Recognition of Older Geez Scripts Written on Vellum
Recognition of handwritten document aims at transforming document images into a machine understandable format. Handwritten document recognition is the most challenging area in the field of pattern recognition. It becomes…
BinarizationHandwritten Document RecognitionSegmentationHigh Density Noise Removal by Cascading Algorithms
An advanced non-linear cascading filter algorithm for the removal of high density salt and pepper noise from the digital images is proposed. The proposed method consists of two stages. The first stage Decision base Media…
Image EnhancementVocal Bursts Intensity PredictionAutomatic Document Image Binarization using Bayesian Optimization
Document image binarization is often a challenging task due to various forms of degradation. Although there exist several binarization techniques in literature, the binarized image is typically sensitive to control param…
Bayesian OptimizationBinarizationTargeted Background Removal Creates Interpretable Feature Visualizations
Feature visualization is used to visualize learned features for black box machine learning models. Our approach explores an altered training process to improve interpretability of the visualizations. We argue that by usi…
Adaptive Weight Modified Riesz Mean Filter For High-Density Salt and Pepper Noise Removal
This paper introduces a novel filter, the Adaptive Weight Modified Riesz Mean Filter (AWMRmF), designed for the effective removal of high-density salt and pepper noise (SPN). AWMRmF integrates a pixel weight function and…
Salt-And-Pepper Noise RemovalSSIM