Adaptive Binarization Method for Enhancing Ancient Malay Manuscript Images

2011 ◽  
pp. 619-627 ◽  
Author(s):  
Sitti Rachmawati Yahya ◽  
Siti Norul Huda Sheikh Abdullah ◽  
Khairuddin Omar ◽  
Choong-Yeun Liong
Keyword(s):  
Binarization Method

An Adaptive Binarization Method for Cost-efficient Document Image System in Wavelet Domain

2020 ◽  
Vol 64 (3) ◽  
pp. 30401-1-30401-14 ◽  
Author(s):  
Chih-Hsien Hsia ◽  
Ting-Yu Lin ◽  
Jen-Shiun Chiang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Document Image ◽  
Background Information ◽  
Raspberry Pi ◽  
Discrete Wavelet ◽  
Image System ◽  
Low Frequencies ◽  
Cost Efficient ◽  
Binarization Method

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.

scholarly journals Application of Zernike moments in computer vision problems for infrared images

2021 ◽  
Vol 310 ◽  
pp. 01002
Author(s):  
Dmitriy Otkupman ◽  
Sergey Bezdidko ◽  
Victoria Ostashenkova
Keyword(s):  
Computer Vision ◽  
Machine Vision ◽  
Thermal Imaging ◽  
Imaging System ◽  
Infrared Region ◽  
Zernike Moments ◽  
Infrared Images ◽  
Theoretical Justification ◽  
Thermal Imaging System ◽  
Binarization Method

The efficiency of using Zernike moments when working with digital images obtained in the infrared region of the spectrum is considered to improve the accuracy and speed of an autonomous thermal imaging system. The theoretical justification of the choice of Zernike moments for solving computer (machine) vision problems and the choice of a suitable threshold binarization method is given. In order to verify the adequacy and expediency of using the chosen method, practical studies were conducted on the use of Zernike methods for distorting various thermal images in shades of gray.

A Lightweight Dynamic Binarization Method for 2D Barcode Scanning Terminal

2011 ◽  
Vol 130-134 ◽  
pp. 4079-4083
Author(s):  
Jia Jia Li ◽  
Ke Liang Zhang ◽  
Gang Wei ◽  
Bai Feng Wu
Keyword(s):  
Density Ratio ◽  
Recognition System ◽  
Gray Level ◽  
Two Dimensional ◽  
2D Barcode ◽  
Space Cost ◽  
Binarization Method ◽  
Local Average ◽  
Number Of Iterations ◽  
Average Gray Level

It is a difficult task to binarize image under uneven illumination, and this problem is always met in the image recognition system, such as two-dimensional barcode scanning terminal. In this paper, an efficient approach is proposed to binarize image which can tolerant uneven illumination and different light intensity. The method initializes thresholds with local average gray level and adjusts thresholds by calculating light density ratio. Due to characteristic of our approach, it can even obtain a sound result by limiting number of iterations which will seriously reduce computations and space cost. According to experiments, we can find that our method can achieve a good performance and meet the real-time requirement and quality demand for barcode scanning terminal.

scholarly journals A db-Scan Hybrid Algorithm: An Application to the Multidimensional Knapsack Problem

Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 507 ◽  
Author(s):  
José García ◽  
Paola Moraga ◽  
Matias Valenzuela ◽  
Hernan Pinto
Keyword(s):  
Transfer Function ◽  
Unsupervised Learning ◽  
Knapsack Problem ◽  
Hybrid Algorithm ◽  
Transfer Functions ◽  
Random Operators ◽  
Multidimensional Knapsack Problem ◽  
Multidimensional Knapsack ◽  
Learning Technique ◽  
Binarization Method

This article proposes a hybrid algorithm that makes use of the db-scan unsupervised learning technique to obtain binary versions of continuous swarm intelligence algorithms. These binary versions are then applied to large instances of the well-known multidimensional knapsack problem. The contribution of the db-scan operator to the binarization process is systematically studied. For this, two random operators are built that serve as a baseline for comparison. Once the contribution is established, the db-scan operator is compared with two other binarization methods that have satisfactorily solved the multidimensional knapsack problem. The first method uses the unsupervised learning technique k-means as a binarization method. The second makes use of transfer functions as a mechanism to generate binary versions. The results show that the hybrid algorithm using db-scan produces more consistent results compared to transfer function (TF) and random operators.

A Stroke Width Based Parameter-Free Document Binarization Method

2015 ◽  
pp. 480-493 ◽  
Author(s):  
Qiang Chen ◽  
Qing Wang ◽  
Sheng-tao Lu ◽  
Yu-ping Wang
Keyword(s):  
Stroke Width ◽  
Binarization Method ◽  
Document Binarization
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