ADVANCES IN WAVELET THEORY AND THEIR APPLICATIONS IN ENGINEERING, PHYSICS AND TECHNOLOGY Edited by Dumitru Baleanu Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology Edited by Dumitru Baleanu Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2012 InTech All chapters are Open Access distributed under the Creative Commons Attribution 3.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. As for readers, this license allows users to download, copy and build upon published chapters even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. Notice Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Vana Persen Technical Editor Teodora Smiljanic Cover Designer InTech Design Team First published April, 2012 Printed in Croatia A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechopen.com Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology, Edited by Dumitru Baleanu p. cm. ISBN 978-953-51-0494-0 Contents Preface IX Part 1 Signal Processing 1 Chapter 1 Real-Time DSP-Based License Plate Character Segmentation Algorithm Using 2D Haar Wavelet Transform 3 Zoe Jeffrey, Soodamani Ramalingam and Nico Bekooy Chapter 2 Wavelet Transform Based Motion Estimation and Compensation for Video Coding 23 Najib Ben Aoun, Maher El’arbi and Chokri Ben Amar Chapter 3 Speech Scrambling Based on Wavelet Transform 41 Sattar Sadkhan and Nidaa Abbas Chapter 4 Wavelet Denoising 59 Guomin Luo and Daming Zhang Chapter 5 Oesophageal Speech’s Formants Measurement Using Wavelet Transform 81 Begona García Zapirain, Ibon Ruiz and Amaia Mendez Chapter 6 The Use of the Wavelet Transform to Extract Additional Information on Surface Quality from Optical Profilometers 99 Richard L. Lemaster Chapter 7 Multi-Scale Deconvolution of Mass Spectrometry Signals 125 M’hamed Boulakroune and Djamel Benatia Part 2 Electrical Systems 153 Chapter 8 Wavelet Theory and Applications for Estimation of Active Power Unbalance in Power System 155 Samir Avdakovic, Amir Nuhanovic and Mirza Kusljugic VI Contents Chapter 9 Application of Wavelet Transform and Artificial Neural Network to Extract Power Quality Information from Voltage Oscillographic Signals in Electric Power Systems 177 R. N. M. Machado, U. H. Bezerra, M. E. L Tostes, S. C. F. Freire and L. A. Meneses Chapter 10 Wavelet Transform in Fault Diagnosis of Analogue Electronic Circuits 197 Lukas Chruszczyk Chapter 11 Application of Wavelet Analysis in Power Systems 221 Reza Shariatinasab and Mohsen Akbari and Bijan Rahmani Chapter 12 Discrete Wavelet Transform Application to the Protection of Electrical Power System: A Solution Approach for Detecting and Locating Faults in FACTS Environment 245 Enrique Reyes-Archundia, Edgar L. Moreno-Goytia, José Antonio Gutiérrez-Gnecchi and Francisco Rivas-Dávalos Part 3 Fault Diagnosis and Monitoring 271 Chapter 13 Utilising the Wavelet Transform in Condition-Based Maintenance: A Review with Applications 273 Theodoros Loutas and Vassilis Kostopoulos Chapter 14 Wavelet Analysis and Neural Networks for Bearing Fault Diagnosis 313 Khalid Al-Raheem Chapter 15 On the Use of Wavelet Transform for Practical Condition Monitoring Issues 353 Simone Delvecchio Part 4 Image Processing 371 Chapter 16 Information Extraction and Despeckling of SAR Images with Second Generation of Wavelet Transform 373 Matej Kseneman and Dušan Gleich Chapter 17 The Wavelet Transform for Image Processing Applications 395 Bouden Toufik and Nibouche Mokhtar Chapter 18 Wavelet Based Image Compression Techniques 423 Pooneh Bagheri Zadeh, Akbar Sheikh Akbari and Tom Buggy Contents VII Chapter 19 Image Denoising Based on Wavelet Analysis for Satellite Imagery 449 Parthasarathy Subashini and Marimuthu Krishnaveni Chapter 20 Image Watermarking in Higher-Order Gradient Domain 475 Ehsan N. Arya, Z. Jane Wang and Rabab K. Ward Chapter 21 Signal and Image Denoising Using Wavelet Transform 495 Burhan Ergen Chapter 22 A DFT-DWT Domain Invisible Blind Watermarking Techniques for Copyright Protection of Digital Images 515 Munesh Chandra Chapter 23 The Wavelet Transform as a Classification Criterion Applied to Improve Compression of Hyperspectral Images 527 Daniel Acevedo and Ana Ruedin Part 5 Applications in Engineering 537 Chapter 24 Robust Lossless Data Hiding by Feature-Based Bit Embedding Algorithm 539 Ching-Yu Yang Chapter 25 Time-Varying Discrete-Time Wavelet Transforms 557 Guangyu Wang, Qianbin Chen and Zufan Zhang Chapter 26 Optimized Scalable Wavelet-Based Codec Designs for Semi-Regular 3D Meshes 567 Shahid M. Satti, Leon Denis, Ruxandra Florea, Jan Cornelis, Peter Schelkens and Adrian Munteanu Chapter 27 Application of Wavelet Analysis for the Understanding of Vortex-Induced Vibration 593 Tomoki Ikoma, Koichi Masuda and Hisaaki Maeda Chapter 28 Application of Wavelets Transform in Rotorcraft UAV’s Integrated Navigation System 613 Lei Dai, Juntong Qi, Chong Wu and Jianda Han Preface Wavelets are functions fulfilling certain mathematical requirements and used in representing data or other functions. The basic idea behind wavelets is to analyze according to scale. Wavelets received considerable attention in the last years because they are very appropriate for application in practical problems in areas of Engineering, Physics and Technology. The book is organized in five main sections denoted as Signal Processing, Electrical Systems, Fault Diagnosis and Monitoring, Image Processing and Applications in Engineering. The wavelet method is used in this book to extract more information than the standard techniques from a given complex signal and it has capabilities for the deconvolution framework. Applications of wavelet transform to the image processing, audio compression and communication systems are also reported. The applications of wavelet transform in the field of power system dynamics and stability, in fault diagnosis of analogue electronic circuits as well as for practical condition monitoring issues are covered by this book. In addition the application of wavelet analysis combined with artificial neural networks as automatic rolling bearing fault detection and diagnosis is illustrated. The use of the wavelet transform to the denoising process is an important chapter of this book. The reader can see how the wavelet transform was used as a classification criterion applied to improve the compression of the hyper-spectral images. The last chapter of the book presents some specific applications of the wavelet transform in engineering, e.g. to robust lossless data hiding by feature-based bit embedding algorithm, for the understanding of vortex-induced vibration, in rotorcraft UAV's integrated navigation system. Also, a constructive design methodology for multi-resolution- scalable mesh compression systems is presented. The chapters of this book present the problems for which wavelet transform is best well-suited, indicates how to implement the corresponding algorithms efficiently, and finally show how to assign the appropriate wavelets for a specified application. X Preface Researchers, working in the field of the wavelet transform, will find several open problems being mentioned within this book. Both theoretical considerations as well as the corresponding applications are clearly presently in such a way to be understandable by a large variety of readers. Dumitru Baleanu Cankaya University, Faculty of Art and Sciences Department of Mathematics and Computer Sciences, Ankara, Turkey Institute of Space Sciences, Magurele-Bucharest, Romania [...]... number of wavelets available in the wavelet family with more being reported in the literature of wavelets (Mallat, 1999) For this application, we are interested in the simplest but efficient DWT The Haar is the first and simplest WT in the family of 10 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology wavelets (Haar, 1911) Haar WT is derived starting with Haar wavelet. .. are mainly applied to LP detection process and benchmarked on baseline processors In this chapter, we have expanded the use of Haar based edges in LP character segmentation algorithm In addition, we have applied these 6 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology edges in HD images and benchmarked their DSP and baseline processor performance to meet real-time... decomposition 14 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology (a) (b) Fig 9 The original license plate candidate image is shown in (a) and prominent edges in the LP candidate are shown in (b) two levels decomposition 4.5 LP character segmentation algorithm The LP character segmentation process follows LP region detection as explained in Section 3.1 In this algorithm... 1 WHigh f n,s f m Ψ * m n f*Ψ Θ [n] j m 0 (10) 8 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology The low frequencies are contained in equation (12), in the computation of periodic scaling filter where the scaling function in equation (11) is sampled with scale z and integer k * (Mallat, 1999) Let Φ Θ [n] Φ k [ n] be a convolution: ... results and analysis Section (7) gives conclusion and Section (8) gives references 4 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology 2 Dedicated hardware for WT review The objective of this work is to investigate a suitable hardware that is able to perform image processing algorithms using WT in real time Processing an image with the WT filter is faster in terms... 12 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology edge angles (Mallat, 1999) Alternatively, an estimate of the wavelet transform modulus of the horizontal and vertical components without taking into account the angle of the DWT as reported in (Qureshi, 2005) In this case, the wavelet modulus is compared to the local average This is the approximation to the wavelet. .. starting with the WT definition 4.1 Wavelet Transform In image processing, we can define a function f(x,y) as an image signal and Ψ(x,y) as a wavelet A wavelet is a function of Ψ Є L2(R) used to localise a given function such as f(x,y) in both translation (u) and scaling (s) The family of wavelet is obtained by translation and scaling in time (t) using individual wavelet as given in equation (1) and. .. Haar WT edges (d) 16 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology The Haar edges are used as a reference without further processing of the Haar edges like thinning; we apply the edges comparison algorithm explained in Section 3.1 and compare location where an edge is verified if a match is found The flow chart is shown in figure 10 The LP candidate has unique... 6.2 Using Haar WT (single level) 95.3 Using Haar WT (two levels) 96.7 Table 1 Algorithm profiling results SD (720x288) HD (1394x1040) Time using DSP (ms) SD (720x288) HD (1394x1040) 6.5 7.6 7.9 8.8 9.1 10.4 10.6 18.2 19.4 22.0 22.6 18 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology It is observed that when using high resolution images and reduced number of wavelet. .. shown in figure 6 and figure 7 respectively (a) (b) Fig 6 The original image is shown in (a) and the resulting image from reconstruction using single level IDWT is shown in (b) (a) (b) Fig 7 Absolute edges are shown on image (a) and image (b) shows prominent edges (a) (b) Fig 8 The original license plate candidate image is shown in (a) and prominent edges in the LP candidate are shown in (b) using single . ADVANCES IN WAVELET THEORY AND THEIR APPLICATIONS IN ENGINEERING, PHYSICS AND TECHNOLOGY Edited by Dumitru Baleanu Advances in Wavelet Theory and Their Applications. applied these Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology 6 edges in HD images and benchmarked their DSP and baseline processor performance to. presents results and analysis. Section (7) gives conclusion and Section (8) gives references. Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology 4 2.