scholarly journals THE USE OF HAAR WAVELETS IN DETECTING AND LOCALIZING TEXTURE DEFECTS

2016 ◽  
Vol 35 (3) ◽  
pp. 195 ◽  
Author(s):  
Gintarė Vaidelienė ◽  
Jonas Valantinas
Keyword(s):  
Defect Detection ◽  
Haar Wavelet ◽  
Haar Wavelets ◽  
Grey Level ◽  
Ceramic Tiles ◽  
New Approach ◽  
Haar Wavelet Transform ◽  
Space Localization ◽  
Texture Defect Detection ◽  
Detection And Localization

In this paper, a new Haar wavelet-based approach to the detection and localization of defects in grey-level texture images is presented. This new approach explores space localization properties of the discrete Haar wavelet transform (HT) and generates statistically-based parameterized texture defect detection criteria. The criteria provide the user with a possibility to control the percentage of both the actually defect-free images detected as defective and/or the actually defective images detected as defect-free, in the class of texture images under investigation. The experiment analyses samples of ceramic tiles, glass samples, as well as fabric scraps, taken from real factory environment.

scholarly journals New Image Compression Algorithm using Haar Wavelet Transform

2017 ◽  
Vol 6 (1) ◽  
pp. 43
Author(s):  
R. El Ayachi ◽  
B. Bouikhalene ◽  
M. Fakir
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Image Compression ◽  
Haar Wavelet ◽  
Compression Algorithm ◽  
Haar Wavelets ◽  
Original Image ◽  
Haar Wavelet Transform ◽  
Compression Coefficient ◽  
Image Compression Algorithm

<p>The compression is a process of Image Processing which interested to change the information representation in order to reduce the stockage capacity and transmission time. In this work we propose a new image compression algorithm based on Haar wavelets by introducing a compression coefficient that controls the compression levels. This method reduces the complexity in obtaining the desired level of compression from the original image only and without using intermediate levels.</p>

scholarly journals Green–Haar wavelets method for generalized fractional differential equations

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Mujeeb ur Rehman ◽  
Dumitru Baleanu ◽  
Jehad Alzabut ◽  
Muhammad Ismail ◽  
Umer Saeed
Keyword(s):  
Differential Equations ◽  
Fractional Differential Equations ◽  
Haar Wavelet ◽  
Haar Wavelets ◽  
Computational Time ◽  
Operational Matrices ◽  
Numerical Techniques ◽  
Fractional Differential ◽  
Fractional Boundary Value Problems ◽  
Better Than

Abstract The objective of this paper is to present two numerical techniques for solving generalized fractional differential equations. We develop Haar wavelets operational matrices to approximate the solution of generalized Caputo–Katugampola fractional differential equations. Moreover, we introduce Green–Haar approach for a family of generalized fractional boundary value problems and compare the method with the classical Haar wavelets technique. In the context of error analysis, an upper bound for error is established to show the convergence of the method. Results of numerical experiments have been documented in a tabular and graphical format to elaborate the accuracy and efficiency of addressed methods. Further, we conclude that accuracy-wise Green–Haar approach is better than the conventional Haar wavelets approach as it takes less computational time compared to the Haar wavelet method.

A detection of defect in diamond images using 2-D haar wavelet transform

ICCAS 2010 ◽  
2010 ◽  
Author(s):  
Puttipong Markchai ◽  
Supaporn Kiattisin ◽  
Adisorn Leelasantitham
Keyword(s):  
Wavelet Transform ◽  
Haar Wavelet ◽  
Haar Wavelet Transform
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