Survey on Document Image Binarization for Degraded Document Images
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 1)Publication Date: 2015-01-05
Authors : Yogita Kakad; Savita Bhosale;
Page : 118-122
Keywords : Adaptive image contrast; document analysis; grey scale method; post processing; document image processing; degraded document image binarization; pixel classification;
Abstract
The Technology is connecting the whole world together by the medium of internet. Each segment of our data is present in the form of digital document. We can able to store, duplicate, and backup our data in digital form. But what we think about old data which is available in the form of traditional document. Sometimes the old documents plays important role in a major challenge. Many of the paper data is being degraded due to lack of attention. Many of these degraded documents have their front data mix up with rear data. To make this front data separate from backend data we have proposed binarized documentation technique. In this we firstly applying the invert contrast mechanism on degraded document. Then we are going to compare that with grey scald edge detection method and then we are applying the binarization method on that degraded image. This binarized image is further undergoes to the post processing module. The output of this all technique will produce a clear and binarized image.
Other Latest Articles
- Bullous Pemphigoid: IGA Autoantibodies Target Epitopes on of Bullous Pemphigoid Antigen 180 Using Recombinant Ectodomains of Collagen XVII
- Biological Control of Bacteria Onion Diseases using a Bacterium, Pantoeaagglomerans 2066-7
- Socio-Economic Conditions of Female Workers in Brick Kilns - An Exploitation to Healthy Social Structure: A Case Study on Khejuri CD Blocks in Purba Medinipur, West Bengal
- Predictive Models for Behavioral Outcomes through Crowdsourcing
- An Intelligent System for Lung Cancer Diagnosis Using Fusion of Support Vector Machines and Back Propagation Neural Network
Last modified: 2021-06-30 21:20:16