Use of wavelet analysis for an objective evaluation of the formation of pills in nonwoven fabrics

2018 ◽  
Vol 49 (5) ◽  
pp. 663-675 ◽  
Author(s):  
Dandan Wang ◽  
JR Barber ◽  
W Lu ◽  
MD Thouless
Keyword(s):  
Wavelet Analysis ◽  
Objective Evaluation ◽  
Digital Data ◽  
Qualitative Assessment ◽  
Background Information ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Nonwoven Fabrics ◽  
Human Interpretation ◽  
Optimal Approach

A quantitative technique to measure pill formation on fabrics has been developed using a wavelet analysis. This technique permits the damage of fabrics to be evaluated with a minimum of human interpretation. A two-dimensional, discrete-wavelet transform was applied to images of nonwoven fabrics, and an optimal approach was found by which the background information could be eliminated from the digital data to obtain characteristic information about the pills. This information, corresponding to the degree of damage, is expressed in terms of a gray-value ratio that is extracted from the details of the wavelet characterization. It has been shown that the resultant parameter correlates well with an independent, qualitative assessment of damage.

Discrete Wavelet Analysis of Two-Dimensional Signals

2002 ◽  
Vol 39 (2) ◽  
pp. 162-174
Author(s):  
F. Asamoah
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Discrete Wavelet Analysis ◽  
Matlab Program

Discrete wavelet transform using Daubechies coefficients is applied to decompose a two-dimensional signal into levels. Examples are given using BMP images of a sheep and a thumbprint. The size of the two- dimensional signal is 2N by M. It is shown that it is not necessary for M to be a power of 2. A MATLAB program is written for the computations involved.

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Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized.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.

Joint Encryption and Compression-Based Watermarking Technique for Security of Digital Documents

2021 ◽  
Vol 21 (1) ◽  
pp. 1-20
Author(s):  
A. K. Singh ◽  
S. Thakur ◽  
Alireza Jolfaei ◽  
Gautam Srivastava ◽  
MD. Elhoseny ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Digital Data ◽  
The Internet ◽  
Discrete Wavelet ◽  
Compression Performance ◽  
Strong Compression ◽  
Multiple Watermarks ◽  
Value Decomposition

Recently, due to the increase in popularity of the Internet, the problem of digital data security over the Internet is increasing at a phenomenal rate. Watermarking is used for various notable applications to secure digital data from unauthorized individuals. To achieve this, in this article, we propose a joint encryption then-compression based watermarking technique for digital document security. This technique offers a tool for confidentiality, copyright protection, and strong compression performance of the system. The proposed method involves three major steps as follows: (1) embedding of multiple watermarks through non-sub-sampled contourlet transform, redundant discrete wavelet transform, and singular value decomposition; (2) encryption and compression via SHA-256 and Lempel Ziv Welch (LZW), respectively; and (3) extraction/recovery of multiple watermarks from the possibly distorted cover image. The performance estimations are carried out on various images at different attacks, and the efficiency of the system is determined in terms of peak signal-to-noise ratio (PSNR) and normalized correlation (NC), structural similarity index measure (SSIM), number of changing pixel rate (NPCR), unified averaged changed intensity (UACI), and compression ratio (CR). Furthermore, the comparative analysis of the proposed system with similar schemes indicates its superiority to them.

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