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Overview of Artifacts Detection and Elimination Methods for BCI Using EEG

Overview of Artifacts Detection and Elimination Methods for ...

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International conference on image, Vision and Computing (ICIVC)

作者： Clifford Maswanganyi Chunling Tu Pius Owolawi Shengzhi Du Department of Computer Systems Engineering Tshwane University of Technology Pretoria Gauteng RSA Department of Electrical Engineering Tshwane University of Technology Pretoria Gauteng RSA

ISBN: (纸本)9781538649923

Electroencephalogram (EEG) is the most commonly utilized method of mapping brain wave patterns from the scalp. It is a process of extracting electrical activities of the brain in the form of EEG signals using non-invasive methods. In EEG based techniques, a challenge exists in the form of signal contamination caused by internal and external factors in the recorded EEG signals., such as the artifacts, interferences among multiple EEG sources, and noise. signal pre-processing is the most significant phase for EEG based applications, for instance, the brain computer interface (BCI) systems. This is because the quality of data acquired from the brain through EEG measurements is dependent on the effectiveness of artifact detection and removal methods. During EEG recording there are several factors that influence the quality of data. One of the factors of signal contamination occurs as the result of physiological and non-physiological artifacts. To detect and remove such contaminations from EEG signals, there are several efficient artifact detection and elimination techniques based on certain pre-processing methods. The main objective of this study is to demonstrate various types of artifacts in EEG recordings as results of external and internal factors. Furthermore, the study will also present an extensive review of existing artifacts identification and elimination methods applied on EEG signals.

关键词： Electroencephalography Physiology Discrete wavelet transforms Electrodes Contamination Electric potential

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An efficient VLSI architecture for fingerprint recognition using O2D-DWT architecture and modified CORDIC-FFT

An efficient VLSI architecture for fingerprint recognition u...

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IEEE International conference on signal processing, Informatics, Communication and Energy Systems (SPICES)

作者： Satish S Bhairannawar Sayantam Sarkar K B Raja K R Venugopal Department of Electronics and Communication Engineering Dayananda Sagar College of Engineering Bangalore India Department of Electronics and Communication Engineering UVCE Banglore India Visvesvaraya College of Engineering Bangalore University Bangalore India

The real time biometric systems are used to authenticate persons for various applications. In this paper, we propose an efficient VLSI architecture for fingerprint recognition using O2D-DWT architecture and modified CORDIC-FFT. The O2D-DWT architecture is designed using only adders and shifters for high speed operation and is applied on fingerprint image to generate four sub-bands. The optimized Fast Fourier Transform (OFFT) architecture is designed by computing different twiddle factor angles using modified CORDIC processor and is applied on LL sub-band coefficients to generate final fingerprint features. The test fingerprint features are compared with features of fingerprint images in database using Euclidean Distance. It is observed that the performance of proposed architecture is better compared to existing architectures.

关键词： Computer architecture Fingerprint recognition Discrete wavelet transforms Finite impulse response filters Databases Very large scale integration

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Digital image watermarking using uncorrelated color space

Digital image watermarking using uncorrelated color space

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International conference on Computer applications and Industrial Electronics (ICCAIE)

作者： Manish Gupta Rajeev Gupta Girish Parmar Mukesh Saraswat University College of Engineering Rajasthan Technical University Kota India University College of Engineering Rajasthan Technical University Sambalpur Odisha IN Motilal Nehru National Institute of Technology Allahabad India

The exponential growths in electronic data over internet have increase the demand of a robust and high quality watermarking method for authentication and copyright protection. The available digital image watermarking methods generally use the correlated color spaces which impose the limitations to researchers for using only one color component at a time for embedding the watermark. Therefore, in this paper, a novel DWT based digital image watermarking method has been proposed which embeds the gray scale watermark into color host image using uncorrelated color space (UCS) and genetic algorithm (GA) method. The result shows that the proposed method outperforms other existing methods against the various signal processing attacks. The proposed method is a first inline report which uses uncorrelated color space for digital image watermarking.

关键词： Watermarking image color analysis Robustness Discrete wavelet transforms Digital images Educational institutions Color

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Projected Improved Fista And Application To image Deblurring

Projected Improved Fista And Application To Image Deblurring

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IEEE International conference on image processing

作者： Praveen Kumar Pokala Chandra Sekhar Seelamantula Department of Electrical Engineering Indian Institute of Science Bangalore India

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

The analysis-sparse model has been shown to be efficient as compared to the synthesis-sparse model when the sparsifying transform is redundant particularly for image restoration applications. We pose the image deblurring problem as an optimization problem based on the analysis-sparse model considering the sparsifying basis to be a tight frame, more specifically, the shift-invariant discrete wavelet transform (SIDWT). We propose two algorithms, namely, projected improved fast iterative soft-thresholding algorithm (piFISTA) and projected improved fast iterative soft-thresholding algorithm beyond Nesterov's momentum (piFISTA-BN). The proposed algorithms are the analysis counterparts of the improved fast iterative soft-thresholding algorithm (iFISTA) and improved fast iterative soft-thresholding algorithm beyond Nesterov's momentum (iFISTA-BN), respectively, both of which consider the synthesis-sparse model. We demonstrate that piFISTA and piFISTA-BN significantly outperform FISTA, pFISTA, iFISTA, and iFISTA-BN considering standard objective metrics such as peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM). Further, we demonstrate empirically that the proposed algorithms converge faster than the state-of-the-art techniques.

关键词： Analytical models image restoration Transforms image reconstruction Iterative algorithms Convergence Standards

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Face Detection using DT-CWT on SHPCA Space

Face Detection using DT-CWT on SHPCA Space

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International conference on Intelligent Systems Design and applications (ISDA)

作者： Yuehui Sun Minghui Du College of Electronic and Information Engineering South China University of Technology Guangzhou China

A novel face detection algorithm is presented by applying dual tree complex wavelets transform (DT-CWT) on spectral histogram PCA space (SHPCA) and support vector machine (SVM). DT-CWT is a transform recently studied, which provides good directional selectivity in six different fixed orientations at different scales. It has limited redundancy for images and is much faster than Gabor transform to compute. Hence, DT-CWT is a good choice to replace Gabor transform in some image signals processing fields especially for face images representation. In the face detection algorithm presented in this paper, images are first projected to SHPCA space after convolved with different filters including DT-CWT filters to achieve features subtraction based on frequency. Then on SHPCA space SVM classification is applied to detect whether faces exist in images or not. The experimental results show that DT-CWT performs much better than Gabor transform on SHPCA space. Furthermore, during preliminary experiments, SVM based on SHPCA space has been trained on a training set of 4000 faces aligned and 6000 non-face images, and a robust classifying function for face and non-face pattern is obtained, which gives the satisfying performance. Several questions about computation time saving and performance improvement are discussed

关键词： Face detection Support vector machines Gabor filters Support vector machine classification wavelet transforms Histograms Principal component analysis signal processing algorithms image representation Frequency

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image Segmentation Based Hybrid Watermarking Algorithm for Copyright Protection

Image Segmentation Based Hybrid Watermarking Algorithm for C...

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International conference on Computing and Networking Technology (ICCNT)

作者： Y. Bhavani Sai Srikar Puppala Spoorthy Shivani Pabba Kavya Sri Kasarla Kadipaka Anvitha Kakatiya Institute of Technology & Science Warangal India

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Today, most of the information shared across the globe is in multimedia form like audio, video and image. With increased globalization, any type of such information can be broadcasted throughout the world easily and is accessible to multiple users for varied applications. This may lead to fraudulent claiming of data ownership which makes copyright protection a major priority in today's world. Digital Watermarking serves as a prime solution to copyright protection where we embed watermark into digital image which serves as an authenticator. In this paper, we proposed a hybrid algorithm using image segmentation, SVD (Singular value decomposition), DWT (Discrete wavelet transformation), Homomorphic filtering and RSA encryption technique that helps to overcome various threats. Here, we proposed a new approach of digital watermarking by embedding two segmented watermarks which are obtained using two distinct threshold values on the original watermark. These threshold values are sent as secret keys to the receiver using Diffie-Hellman key exchange algorithm and can be used at the time of copyright verification. This approach of hybrid technique is being tested by applying Gaussian Noise and it gave the best results when compared with the other digital watermarking techniques.

关键词： Watermarking Discrete wavelet transforms image segmentation signal processing algorithms Discrete cosine transforms Hafnium Copyright protection

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The design of MAC unit for DWT implementation

The design of MAC unit for DWT implementation

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International conference on Microelectronics, ICM

作者： C. Souani M. Abid K. Torki R. Tourki Electronics & Micro-Electronics Laboratory Faculty of Sciences of Monastir Tunisia TIMA-CMP Laboratory Grenoble France

High performance FIR filters have applications in several video processing and digital communications systems. Audio and telecommunication applications may use filters at sample rates of 10-30 MHz. High-speed digital data communications or high rate video transmission systems may need preferment filters. This paper deals with the VLSI implementation of a recursive filter. The designed device will he used as a sub-element for the design of a DWT circuit. The performance of the DWT circuit depend on the performance of the MAC unit.

关键词： Discrete wavelet transforms Finite impulse response filter Filter bank Digital filters Adaptive filters Circuits Application software image coding signal resolution Low pass filters

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High speed low power DWT structure with log based FPU in FPGAs

High speed low power DWT structure with log based FPU in FPG...

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International conference on Green Computing, Communication and Conservation of Energy (ICGCE)

作者： D. Vaithiyanathan R. Seshasayanan Dept. of Electronics and Communication Engineering Anna University Chennai India

ISBN: (纸本)9781467361248

wavelet transforms have become one of the basic tools of signal and image processing, digital communications and other applications. Biorthogonal wavelet transform attains further more importance as it allows the construction of symmetric wavelet, which provides the linear phase filter. As the lossy biorthogonal 9/7 (B9/7) transform uses floating point lifting coefficients, the computational complexity of the overall structure gets increased as the levels are increased. This leads to unwanted increment in additional latency in the overall circuit and also hardware realization leads to increased area and power consumption. Hence in this paper, we propose an alternate structure for arithmetic computations involved in the B9/7 DWT which utilizes the power saving attribute of Logarithmic Number Systems (LNS). This LNS adaptation in arithmetic unit results in overall accuracy enhancement with reduced area and power consumption. We also explored the constituent latency and found that the main memory access for the input feed is one of the main factors that increase the latency in the circuit. Hence, we attain a feasible solution of segregating the main memory from the structure, and inputs are fed from temporary memory blocks to the structure. Hence, symmetric extension of the image to be transformed is handled in a way that does not require additional computation or clock cycles; it is expected to provide a reduction in hardware complexity and increase in computational speed. We evaluated the performance and correctness of the architecture by implementing in Xilinx Virtex 6 field programmable gate arrays.

关键词： Discrete wavelet transforms Accuracy PSNR Delays Field programmable gate arrays

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Artificial intelligence for pattern recognition in automated surface engineering

Artificial intelligence for pattern recognition in automated...

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International conference on Systems and Informatics (ICSAI)

作者： E. Sheybani S. Garcia-Otero F. Adnani G. Javidi DSP Laboratory Virginia State University Petersburg VA USA

Ability to measure the surface quality in real-time has many applications in manufacturing automation and product optimization, especially in processes in which the surface qualities such as roughness, grain size, thickness of coding, impurities size and distribution, hardness, and other mechanical properties are of importance. Surface analysis in manufacturing environments requires specialized filtering techniques. Due to the immense effect of rough environment and corruptive parameters, it is often impossible to evaluate the quality of a surface that has undergone various grades of processing. The algorithm presented here is capable of performing this comparison analytically and quantitatively at a low computational cost (real-time) and high efficiency. The parameters used for comparison are the degree of blurriness and the amount of various types of noise associated with the surface image. Based on a heuristic analysis of these parameters the algorithm assesses the surface image and quantifies the quality of the image by characterizing important aspects of human visual quality. Extensive effort has been set forth to obtain real-world noise and blur conditions so that the various test cases presented here could justify the validity of this approach well. The tests performed on the database of images produced valid results for the proposed algorithm consistently. This research aims at providing image processing tools for comparison and assessment of a surface processed under different grades of a manufacturing process all the way up to optimal processing. This paper presents the description and validation (along with test results) of the proposed algorithm for surface image quality assessment.

关键词： Surface treatment Noise Algorithm design and analysis Filter banks image quality signal processing algorithms wavelet transforms

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Improving Block Matching and 3 Dimensions (BM3D) Filtering for image Noise Removal Using Discrete wavelet Transformation (DWT)

Improving Block Matching and 3 Dimensions (BM3D) Filtering f...

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Sciences and Techniques of Automatic Control and Computer Engineering MI-STA, IEEE International Maghreb Meeting of the conference on

作者： Warda Kshem Asem Khmag Department of Computer Engineering Faculty of Engineering University of Zawia Az zawia Libya

ISBN: (数字)9798350372632

ISBN: (纸本)9798350372649

In the field of image denoising, Block Matching 3 Dimensions technique (BM3D) stated as a powerful technique that works to remove white Gaussian noise (A WGN). Despite BM3D shows its great success in comparison with the best denoising methods, still its visual quality decreases as the noise density escalates in noisy digital images. Therefore, the need to create a powerful image denoising method is necessary to accomplish the processing of image enhancement applications. The proposed method is introduced by. In this study, discrete wavelet transformation is applied on the LL level of the wavelet decomposition due to its ability to keep the smallest change in the original image. Furthermore, the coefficients of LL will be then divided to small blocks that contain contaminated pixels that suffer from additive white Gaussian noise (A WGN). Comparing with conventional block matching 3D (BM3D) that works well only on the similar patches, our proposed method has the ability to work on similar and dissimilar patches in order to find the inter and intra- correlations between dissimilar pixels. The proposed technique is examined on several digital benchmark images with different noise levels in terms of the quantity of the lost in the original and resulted pixels. In this regard, the performance of the tested images is estimated and then compared proposed with several high quality noise removal techniques according to several assessments such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and the figure of merits (FOM). The high amount of these factors reflects the success of the proposed technique. Further, it is interesting to observe the improvement in the running time where it was far less than the investigated noise removal algorithms.

关键词： Visualization Correlation PSNR Three-dimensional displays Noise Estimation Discrete wavelet transforms

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