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The effects on classifier performance of 2d discrete wavelet transform analysis and whale optimization algorithm for recognition of power quality disturbances

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COGNITIVE SYSTEMS RESEARCH 2022年 75卷 1-15页

作者： Karasu, Seckin Sarac, Zehra Zonguldak Bulent Ecevit Univ Elect & Elect Engn Dept TR-67100 Zonguldak Turkey Istanbul Medeniyet Univ Elect & Elect Engn Dept TR-34700 Istanbul Turkey

Power Quality (PQ) is becoming more and more important day by day in the electric network. Signal processing, pattern recognition and machine learning are increasingly being studied for the automatic recognition of any disturbances that may occur during the generation, transmission, and distribution of electricity. There are three main steps to identify the PQ disturbances. These include the use of signal processing methods to calculate the features representing the disturbances, the selection of those that are more useful than these feature sets to prevent the creation of a complex classification model, the creating a classification model that recognizes multiple classes using the selected feature subsets. In this study, one-dimensional (1d) PQ disturbances signals are transformed into two-dimensional (2d) signals, 2d discrete wavelet transforms (2d-dWT) are used to extract the features. The features are extracted by using the wavelet families such as daubechies, Biorthogonal, Symlets, Coiflets and Fejer-Korovkin in 2d-dWT to analyze PQ disturbances. Whale Optimization Algorithm (WOA) and k-nearest neighbor (KNN) classifier determine the feature subsets. Then, WOA and k nearest neighbor (KNN) classifier are used to determine the feature group. By using KNN and Support Vector Machines (SVM) classifi-cation methods, Classifier models that distinguish PQ disturbances are formed. The main aim of the study is to determine the features derived from 2d wavelet coefficients for different wavelet families and to determine which of them has a better classification performance to distinguish PQ disturbances signals. At the same time, different classification methods are simulated and a model which can classify PQ disturbances signals with high performance is created. Also, the generated models are analysed for their performance in terms of different noise levels (40 dB, 30 dB, 20 dB). The result of this simulation study shows that the model developed to classify PQ disturbanc

关键词： Power quality disturbances 2d discrete wavelet transform wavelet families Whale optimization algorithm 2d signal processing Evolutionary feature selection

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FPGA implementation for 2d discrete wavelet transform

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ELECTRONICS LETTERS 1998年第7期34卷 639-640页

作者： Hung, KC Huang, YJ Truong, TK Wang, CM Dept. of Electron. Eng. I-Shou Univ. Taiwan

An operator correlation-based algorithm and its VLSI architecture for computing the 2d discrete wavelet transform is presented. The proposed discrete wavelet transform architecture was simulated in Verilog and synthesised with the FPGA compiler. The implementation for the 2d discrete wavelet transform on an FPGA-based design style is described.

关键词： 2d discrete wavelet transform FPGA VLSI VLSI architecture Verilog simulation field programmable gate arrays operator correlation algorithm wavelet transforms

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Still image compression based on 2d discrete wavelet transform

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ELECTRONICS LETTERS 1999年第22期35卷 1934-1935页

作者： Tan, RHG Zhang, JF Morgan, R Greenwood, A Liverpool John Moores Univ Sch Engn Liverpool L3 3AF Merseyside England

The objective of this Letter is to develop new techniques for enhancing the compression of still images. The features of the proposed algorithm include: (i) zero mapping, which exploits the inherent self-similarity of wavelet coefficients at different scales, (ii) adaptive scanning, and (iii) data packing. Our algorithm outperforms both JPEG and the embedded zerotree wavelet (EZW) algorithm.

关键词： still image compression discrete wavelet transforms Image and video coding inherent self-similarity data compression adaptive scanning Integral transforms in numerical analysis 2d discrete wavelet transform image coding data packing wavelet coefficients zero mapping Computer vision and image processing techniques

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Colour-image encryption based on 2d discrete wavelet transform and 3d logistic chaotic map

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JOURNAL OF MOdERN OPTICS 2020年第10期67卷 933-949页

作者： Joshi, Anand B. Kumar, dhanesh Mishra, d. C. Guleria, Vandana Univ Lucknow Dept Math & Astron Lucknow Uttar Pradesh India Govt PG Coll Jaiharikhal Dept Math Uttrakhand India Birla Inst Technol Mesra Dept Math Ranchi Bihar India

This paper proposes a new lossless encryption and decryption method for digital colour-image using 2d discrete Haar wavelet transform (dHWT) and 3d logistic chaotic map. The proposed cryptosystem provides the security of the digital images using the cryptographic algorithm in the frequency domain of the image. The proposed method uses two levels of 2d dHWT for the decomposition of the image. For the encryption, 2d dHWT is applied on the different colour components of the colour-image and then the encryption method is applied on the different sub-bands of each level of decomposition and for the decryption the reverse process of the encryption is used with the inverse of functions used in encryption. The experimental results and the security analysis like brute force analysis, statistical analysis, occlusion and differential attack of the proposed method are given to validate the feasibility and robustness of the method.

关键词： 2d discrete wavelet transform 3d logistic chaotic map Haar wavelet transform colour-image encryption image decryption lossless encryption

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A novel encryption scheme for securing biometric templates based on 2d discrete wavelet transform and 3d Lorenz-chaotic system

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RESULTS IN OPTICS 2021年 5卷

作者： Kumar, dhanesh Joshi, Anand B. Singh, Sonali Univ Lucknow Dept Math & Astron Lucknow UP India

This research paper proposes a novel encryption and decryption scheme for biometric templates using two dimensional discrete wavelet transform (2d-dWT) and three dimensional (3d) Lorenz-chaotic system. In the proposed scheme two levels of 2d-dWT are used for the decomposition of the group representation of the different biometric templates and then substitution and permutation are applied using some mechanism and 3d Lorentz-chaotic system. The encryption scheme is applied on the different sub-bands of each level of decomposition, and for the decryption, the reverse process of the encryption is used. The experimental results, biometric template matching, security analysis, and statistical analysis of the proposed scheme are given to validate the robustness of the scheme. The security analysis shows that the brute-force attack is not possible in the proposed scheme.

关键词： 2d discrete wavelet transform 3d Lorenz-chaotic system Haar transform Biometric template encryption decryption

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Compression of multi-polarimetric SAR intensity images based on 3d-matrix transform

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IET IMAGE PROCESSING 2008年第4期2卷 194-202页

作者： Zhang, W. -C. Wang, Y. -F. Hu, G. -H. Chinese Acad Sci Inst Elect Beijing 100080 Peoples R China Chinese Acad Sci Grad Sch Beijing 100039 Peoples R China

The algorithms for multi-polarimetric synthetic aperture radar (SAR) intensity image compression are investigated. First, the multi-polarimetric SAR intensity images (HH, HV and VV) are considered as a 3d-matrix unit, and then a 3d-matrix transform is adopted to remove the redundancies, which includes 1d discrete cosine transform (dCT) in the polarimetric channels and 2d discrete wavelet transform (dWT) in each polarimetric SAR image plane. After the 3d-matrix transform, two methods are proposed to encode the 3d mixed coefficients. One is a bit allocation encoding based on differential entropy and the other is a 3d set partitioning in hierarchical trees (SPIHT) encoding which is an improvement of the conventional SPIHT. The two methods can remove not only the redundancies of the image inside but also the redundancies among the polarimetric channels, because they do not process every channel image separately. Both the theory and experimental results show that the proposed methods are efficient.

关键词： SPIHT encoding polarimetric channels discrete cosine transforms 3d-matrix transform Radar equipment, systems and applications 3d set partitioning in hierarchical trees tree codes data compression 2d discrete wavelet transform Image and video coding image coding Integral transforms dCT Algebra discrete wavelet transforms radar polarimetry matrix algebra images compression synthetic aperture radar multipolarimetric SAR intensity images dWT radar imaging discrete cosine transform 3d mixed coefficients differential entropy

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2-d dWT/IdWT processor design for image coding

2-D DWT/IDWT processor design for image coding

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2nd International Conference on ASIC

作者： Chen, XY Zhou, T Zhang, QL Min, H ASIC & Systems State-key Laboratory Fudan University Shanghai China Fudan University Shanghai Shanghai CN

ISBN: (纸本)7543909405

In this paper, a VLSI architecture for forward inverse 2-d discrete wavelet transform is presented. This design described and verified by the VHdL is synthesized by the Synopsys-synthesizer. The synthesis results show that the gate-level circuit contains 7140 gates and the throughput can reach 4 M pixel/s when LSI_10K CMOS process technology is used.

关键词： image coding wavelet transforms digital signal processing chips VLSI integrated circuit design hardware description languages CMOS digital integrated circuits inverse problems image coding VLSI architecture 2d discrete wavelet transform VHdL synthesis Synopsys gate-level circuit LSI CMOS technology inverse 2d discrete wavelet transform processor design

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Illumination compensation for face recognition using adaptive singular value decomposition in the wavelet domain

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INFORMATION SCIENCES 2018年 435卷 69-93页

作者： Wang, Jing-Wein Ngoc Tuyen Le Lee, Jiann-Shu Wang, Chou-Chen Natl Kaohsiung Univ Appl Sci Inst Photon & Commun Kaohsiung 813 Taiwan Hung Yen Univ Technol & Educ Fac Informat Technol Khoai Chau 160000 Hung Yen Vietnam Natl Univ Tainan Dept Comp Sci & Informat Engn Tainan 700 Taiwan I Shou Univ Dept Elect Engn Kaohsiung 840 Taiwan

Lighting variations are a challenge in face recognition. To overcome this problem, this paper proposes a novel illumination compensation method called adaptive singular value decomposition in the 2d discrete wavelet domain (ASVdW) to enhance face images. First, an efficient brightness detector based on the blue pixel values of the red green blue (RGB) color channels is used to classify the color face image into dark, normal, or bright before applying the corresponding Gaussian template. The RGB color channels of the face image are then transformed to the 2d discrete wavelet domain. The frequency subband coefficients of the three color channels are automatically adjusted by multiplying the singular value matrices of these frequency subband coefficient matrices with their corresponding compensation weight coefficients. An efficient image denoising model is then applied, and a 2d inverse discrete wavelet transform is applied to obtain the ASVdW-compensated color face images without the lighting effect. In addition, a region-based ASVdW method (RASVdW), which entails the application of the ASVdW algorithm in four regions of an image, is introduced to reduce the computing time. Experimental results validate the efficiency of the proposed methods. (C) 2018 Elsevier Inc. All rights reserved.

关键词： 2d discrete wavelet transform Face recognition Illumination compensation Singular value decomposition

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Nonwoven uniformity identification using wavelet texture analysis and LVQ neural network

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EXPERT SYSTEMS WITH APPLICATIONS 2010年第3期37卷 2241-2246页

作者： Liu, Jianli Zuo, Baoqi Zeng, Xianyi Vroman, Philippe Rabenasolo, Besoa Soochow Univ Coll Text & Clothing Engn Suzhou 215021 Peoples R China Univ Lille Nord France F-59000 Lille France GEMTEX ENSAIT F-59056 Roubaix France

In this paper, an approach to grade nonwoven uniformity by combining wavelet texture analysis and learning vector quantization (LVQ) neural network is proposed. Six hundred and twenty-five nonwoven images of five different grades, 125 images of each grade, are decomposed at four different levels with five wavelet bases of daubechies family, and two kinds of energy values L(1) and L(2) extracted from the high frequency subbands are used as the input features of the LVQ neural network solely and jointly. For each grade, 60 comparative experiments are employed to evaluate the performance of our method, which takes into account three effect factors, wavelet base (the length of filter), decomposition level and feature set. Experimental results on the 625 nonwoven images indicate that just use L(1) as feature calculated with db(6), at level 3, the identification accuracy of grade A, grade C and grade E are 100%. When the nonwoven images are decomposed at level 3, the minimal average identification accuracy of five grades with five different wavelet bases is 87.7%. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Nonwovens uniformity 2d discrete wavelet transform wavelet texture analysis LVQ neural network

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Enhanced Ridge Structure for Improving Fingerprint Image Quality Based on a wavelet domain

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IEEE SIGNAL PROCESSING LETTERS 2015年第4期22卷 390-394页

作者： Wang, Jing-Wein Ngoc Tuyen Le Wang, Chou-Chen Lee, Jiann-Shu Natl Kaohsiung Univ Appl Sci Inst Photon & Commun Kaohsiung 807 Taiwan I Shou Univ Dept Elect Engn Kaohsiung 840 Taiwan Natl Univ Tainan Dept Comp Sci & Informat Engn Tainan 700 Taiwan

Fingerprint image enhancement is one of the most crucial steps in an automated fingerprint identification system. In this paper, an effective algorithm for fingerprint image quality improvement is proposed. The algorithm consists of two stages. The first stage is decomposing the input fingerprint image into four subbands by applying two-dimensional discrete wavelet transform. At the second stage, the compensated image is produced by adaptively obtaining the compensation coefficient for each subband based on the referred Gaussian template. The experimental results indicated that the compensated image quality was higher than that of the original image. The proposed algorithm can improve the clarity and continuity of ridge structures in a fingerprint image. Therefore, it can achieve higher fingerprint classification rates than related methods can.

关键词： 2d discrete wavelet transform fingerprint classification fingerprint enhancement singular value decomposition

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