scholarly journals A Survey on Binarization Technique for Degraded Documents

Author(s):  
Kirti Tomar
Keyword(s):  
2008 ◽  
Vol 18 (05) ◽  
pp. 405-418 ◽  
Author(s):  
ADNAN KHASHMAN ◽  
BORAN SEKEROGLU

Advances in digital technologies have allowed us to generate more images than ever. Images of scanned documents are examples of these images that form a vital part in digital libraries and archives. Scanned degraded documents contain background noise and varying contrast and illumination, therefore, document image binarisation must be performed in order to separate foreground from background layers. Image binarisation is performed using either local adaptive thresholding or global thresholding; with local thresholding being generally considered as more successful. This paper presents a novel method to global thresholding, where a neural network is trained using local threshold values of an image in order to determine an optimum global threshold value which is used to binarise the whole image. The proposed method is compared with five local thresholding methods, and the experimental results indicate that our method is computationally cost-effective and capable of binarising scanned degraded documents with superior results.


2016 ◽  
Vol 3 (3) ◽  
pp. 27
Author(s):  
HARSHMANI ◽  
GUPTA NANCY ◽  
KAUR GURPREET ◽  
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...  

2021 ◽  
Author(s):  
N Shobharani ◽  
Bipin Nair B J ◽  
Karthik S K ◽  
Srinidhi A

Author(s):  
Soharab Hossain Shaikh ◽  
Ayan Dey ◽  
Khalid Saeed ◽  
Nabendu Chaki

Author(s):  
MICHAEL MAKRIDIS ◽  
N. PAPAMARKOS

This paper presents a new technique for adaptive binarization of degraded document images. The proposed technique focuses on degraded documents with various background patterns and noise. It involves a preprocessing local background estimation stage, which detects for each pixel that is considered as background one, a proper grayscale value. Then, the estimated background is used to produce a new enhanced image having uniform background layers and increased local contrast. That is, the new image is a combination of background and foreground layers. Foreground and background layers are then separated by using a new transformation which exploits efficiently, both grayscale and spatial information. The final binary document is obtained by combining all foreground layers. The proposed binarization technique has been extensively tested on numerous documents and successfully compared with other well-known binarization techniques. Experimental results, which are based on statistical, visual and OCR criteria, verify the effectiveness of the technique.


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