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2012 International Conference on Advances in Computing and Communications, ICACC 2012

作者： Indukala, P.K. Lakshmi, K. Sowmya, V. Soman, K.P. Center for Excellence in Computational Engineering and Networking Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore 641112 Tamilnadu India

ISBN: (纸本)9780769547237

Compressed sensing helps in the reconstruction of sparse or compressible signals from small number of measurements. The sparse representation has great importance in modern signal processing. The main objective is to provide a strong understanding of the concept behind the theory of compressed sensing by using the key ideas from linear algebra. In this paper, the concept of compressed sensing is explained through an experiment formulated based on linear programming and solved using l1 magic and One bit compressed sensing methods in Excel. © 2012 IEEE.

关键词： Compressed sensing

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Performance Study of Active Contour Model Based Character Segmentation with Nonlinear Diffusion

Performance Study of Active Contour Model Based Character Se...

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International Conference on Advances in Computing and Communications (ICACC)

作者： K. Syama Nikitha George Swathy Sekhar C.S. Neethu M. Sabarimalai Manikandan K.P. Soman Center for Excellence in Computational Engineering and Networking Amrita Viswavidyapeetham University Tamil Nadu India

In this paper, we present the combined character segmentation algorithm based on the active contour model and nonlinear diffusion techniques. The active contour model is used to perform segmentation of printed characters. The coherence enhancing diffusion technique is proposed to smooth out artifacts and background noises without destroying the edges. The performance of the two character segmentation methods: i) the combined ACM-FGM and CED algorithm, and ii) the ACM-FGM algorithm have been validated using a large scale printed documents in Hindi, Malayalam and Telugu text. The combined algorithm achieves an average segmentation accuracy of 89.08% whereas the ACM-FGM algorithm alone had an average accuracy of 52.63%. The whole character segmentation process time is lesser than that of the ACM-FGM algorithm alone. Experiments show that the combined algorithm provides promising results under scanned documents with different font-size and fond-style characters, and the different artifacts and background noises caused by the aging of the paper and diffusion.

关键词： Image segmentation Noise measurement Accuracy Active contours Optical character recognition software Image edge detection Coherence

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Image denoising solutions using heat diffusion equation

Image denoising solutions using heat diffusion equation

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International Conference on Power, Signals, Controls and Computation (EPSCICON)

作者： K Lakshmi R Parvathy S Soumya K. P. Soman Center for Excellence in Computational Engineering and Networking (CEN) Amrita Vishwa Vidyapeetham Coimbatore India

The idea of this paper is to model image denoising using an approach based on partial differential equations (PDE), which describes two dimensional heat diffusion. The two dimensional image function is taken to be the harmonic, when it can be obtained as the solution to the equation describing the the heat diffusion. To achieve this, image denoising is formulated as an optimization problem, in which a function with two terms is to be minimized. The first term is called the regularization term, which is some form of energy of the image (like Sobolev energy) and the second term is called the data fidelity term, which measures the similarity between the original image and the processed image. The two terms are combined using a control parameter whose value decides which term has to be minimized more. Image denoising problem could then be solved by a simple iterative equation, derived based on the Gradient Descent method.

关键词： Mathematical model Noise reduction Heating Equations Image denoising Noise

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An Efficient R-peak Detection Based on New Nonlinear Transformation and First-Order Gaussian Differentiator

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Cardiovascular engineering and Technology 2011年第4期2卷 408-425页

作者： Kathirvel, P. Manikandan, M. Sabarimalai Prasanna, S.R.M. Soman, K.P. Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore 641105 India Center for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore Tamilnadu India Department of Electrical and Electronics Engineering Indian Institute of Technology Guwahati Guwahati Assam India

In this paper, we present a reliable and efficient automatic R-wave detection based on new nonlinear transformation and simple peak-finding strategy. The detection algorithm consists of four stages. In the first stage, the bandpass filtering and differentiation operations are used to enhance QRS complexes and to reduce out-of-band noise. In the second stage, we introduce a new nonlinear transformation based on energy thresholding, Shannon energy computation, and smoothing processes to obtain a positive-valued feature signal which includes large candidate peaks corresponding to the QRS complex regions. The energy thresholding reduces the effect of spurious noise spikes from muscle artifacts. The Shannon energy transformation amplifies medium amplitudes and results in small deviations between successive peaks. Therefore, the proposed nonlinear transformation is capable of reducing the number of false-positives and false-negatives under small-QRS and wide-QRS complexes and noisy ECG signals. In the third stage, we propose a simple peak-finding strategy based on the firstorder Gaussian differentiator (FOGD) that accurately identifies locations of candidate R-peaks in a feature signal. This stage computes convolution of the smooth feature signal and FOGD operator. The resultant convolution output has negative zero-crossings (ZCs) around the candidate peaks of feature signal due to the anti-symmetric nature of the FOGD operator. Thus, these negative ZCS are detected and used as guides to find locations of real R-peaks in an original signal at the fourth stage. Unlike other existing algorithms, the proposed algorithm does not use search back algorithm and learning phase. The proposed algorithm is validated using the standard MIT-BIH arrhythmia database and achieves an average sensitivity of 99. 94% and a positive predictivity of 99.96%. Experimental results show that the proposed algorithm outperforms other existing algorithms in case of different QRS complex morphologies

关键词： Convolution

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Automated cardiac event change detection for continuous remote patient monitoring devices 11

Automated cardiac event change detection for continuous remo...

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1st International Conference on Wireless Technologies for Humanitarian Relief, ACWR 2011

作者： Baby, Britty Manikandan, M. Sabarimalai Soman, K.P. Department of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Tamilnadu 641112 India Center for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Tamilnadu 641112 India

ISBN: (纸本)9781450310116

Recently, wireless body area network (WBAN) plays an important role in remote cardiac patient monitoring, and mobile healthcare applications. Generally, the use of WBAN technology is restricted by size, power consumption, transmission capacity (bandwidth), and computational loads. In this paper, we therefore propose an automated cardiac event change detection for continuous remote patient monitoring devices. The proposed event change detection algorithm consists of two stages: i) ECG beat extraction;and ii) ECG beat similarity measure. In the first stage, the onset of each QRS complex is identified using the Gaussian derivative based QRS detector and the two heuristics rules. In the second stage, we employ the weighted wavelet distance (WWD) metric for finding the similarity between two ECG beats in wavelet domain. The WWD is the weighted normalized Euclidean wavelet distance between the wavelet subband coefficients vectors of the current and past ECG beats, where weights are equal to the relative wavelet subband energies of the corresponding subbands. The experimental results show that the weighted wavelet distance measure works substantially better than the conventional PRD and the wavelet based weighted PRD (WWPRD) measures under noisy environments. The proposed approach has been tested and yielded an accuracy of 99.76% on MIT-BIH Arrhythmia Database.

关键词： Electrocardiograms

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Quality-driven wavelet based PCG signal coding for wireless cardiac patient monitoring 11

Quality-driven wavelet based PCG signal coding for wireless ...

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1st International Conference on Wireless Technologies for Humanitarian Relief, ACWR 2011

作者： Sabarimalai Manikandan, M. Soman, K.P. Dandapat, S. Center for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore Campus 641112 India Department of Electrical and Electronics Engineering Indian Institute of Technology Guwahati Assam 781039 India

ISBN: (纸本)9781450310116

In this paper, we present a quality driven PCG signal coding scheme for wireless cardiac patient monitoring applications. The proposed quality driven codec is designed based on the wavelet-based compression method and the wavelet energy based diagnostic distortion (WEDD) measurement criterion. The proposed WEDD measure is the weighted percentage root mean square difference between the wavelet subband coefficients of the original and compressed signals with weights equal to the relative wavelet subband energies of the corresponding subbands. The WEDD measure appears to be a correct representation of the amount of signal distortion at all the subbands, and robust to insignificant errors in some bands. The performance of the proposed method is validated using the PCG signal blocks taken from the qdheart database and CAHM database PCG records which include many different valvular pathologies such as normal sounds, late systolic, ejection click, tricuspid regurgitation, diastolic aortic insufficiency, murmurs, and noises. Results showed that the performance of the WEDD criterion outperforms the PRDw and WWPRD criteria. For WEDD=4%, the maximum compression ratio of 186.07 was achieved for the test signal from the Diastolic Fixed S2 Split II record and the minimum compression ratio of 21.16 is obtained for the signal from the Diastolic Atrial Septal Defect record.

关键词： Patient monitoring

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Generalised and Channel Independent SVM Based Robust Decoders for Wireless Applications

Generalised and Channel Independent SVM Based Robust Decoder...

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International Conference on Advances in Recent Technologies in Communication and Computing, ARTCom

作者： R. Ramanathan K.P. Soman N. Valliappan S. Pon Mathavan M. Gayathri R. Priya Department of Electronics & Communication Engineering Amrita Viswavidyapeetham University Coimbatore India Center for Excellence in Computational Engineering and Networking (CEN) Amrita Viswavidyapeetham University Coimbatore India

Emerging applications in wireless communications and software defined radio require robust and generalized decoders with a very good efficiency. This paper aims at introducing a novel and powerful method of implementing a decoder using support vector machines (SVM) to exhibit good performance irrespective of the channel model. The method proposed also ensures a generalization in the design of decoder, which can be easily adaptable for any type of coding technique used. In addition, this method overcomes the demerits of the traditional decoders like Viterbi and other decoders using neural networks. The error correction codes like Hamming and convolutional codes are considered for experimentation. Using SVM, which is a class of machine learning algorithm, this process is viewed as a multi-class classification problem and error correction is achieved in a simpler way. An extensive analysis with regard to the effect of channel and modulation techniques is also made and presented. The proposed SVM model is sufficiently cross validated and found to be an effective replacement for the existing counterparts.

关键词： Support vector machines Robustness Decoding Application software Support vector machine classification Wireless communication Software radio Viterbi algorithm Neural networks Error correction codes

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Tamil Font Recognition Using Gabor Filters and Support Vector Machines

Tamil Font Recognition Using Gabor Filters and Support Vecto...

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International Conference on Advances in Computing, Control, & Telecommunication Technologies (ACT)

作者： R. Ramanathan S. Ponmathavan L. Thaneshwaran Arun S. Nair N. Valliappan K.P. Soman Department of Electronics & Communication Engineering Amrita Viswavidyapeetham University Coimbatore India Center of Excellence in Computational Engineering and Networking (CEN) Amrita Viswavidyapeetham University Coimbatore India

Tamil Font Recognition is one of the Challenging tasks in Optical Character Recognition and Document Analysis. Most of the existing methods for font recognition make use of local typographical features and connected component analysis. In this paper, Tamil font recognition is done based on global texture analysis. The main objective of this proposal is to employ support vector machines (SVM) in identifying various fonts in Tamil. The feature vectors are extracted by making use of Gabor filters and the proposed SVM is trained using these features. The method is found to give superior performance over neural networks by avoiding local minima points. The SVM model is formulated tested and the results are presented in this paper. It is observed that this method is content independent and the SVM classifier shows an average accuracy of 92.5%.

关键词： Gabor filters Support vector machines Support vector machine classification Character recognition Optical character recognition software Optical filters Text analysis Proposals Feature extraction Neural networks

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A Novel Technique for English Font Recognition Using Support Vector Machines

A Novel Technique for English Font Recognition Using Support...

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International Conference on Advances in Recent Technologies in Communication and Computing, ARTCom

作者： R. Ramanathan K.P. Soman L. Thaneshwaran V. Viknesh T. Arunkumar P. Yuvaraj Department of Electronics & Communication Engineering Amrita Viswavidyapeetham University Coimbatore India Center for Excellence in Computational Engineering and Networking (CEN) Amrita Viswavidyapeetham University Coimbatore India

Font Recognition is one of the Challenging tasks in Optical Character Recognition. Most of the existing methods for font recognition make use of local typographical features and connected component analysis. In this paper, English font recognition is done based on global texture analysis. The main objective of this proposal is to employ support vector machines (SVM) in identifying various fonts. The feature vectors are extracted by making use of Gabor filters and the proposed SVM is trained using these features. The method is found to give superior performance over neural networks by avoiding local minima points. The SVM model is formulated tested and the results are presented in this paper. It is observed that this method is content independent and the SVM classifier shows an average accuracy of 93.54%.

关键词： Support vector machines Support vector machine classification Character recognition Optical character recognition software Optical filters Proposals Feature extraction Gabor filters Neural networks Testing

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Improved Technique for the Construction of Parametric M-Band Wavelets

Improved Technique for the Construction of Parametric M-Band...

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International Conference on Advances in Recent Technologies in Communication and Computing, ARTCom

作者： R. Ramanathan K.P. Soman Department of Electronics & Communication Engineering Amrita Viswavidyapeetham University Coimbatore India Center for Excellence in Computational Engineering and Networking (CEN) Amrita Viswavidyapeetham University Coimbatore India

Demanding applications of wavelets in OFDM modulation, watermarking, cognitive radio and wireless networks has created an immense interest amongst the researchers to work on the design of good wavelet system. Parametric and M-band wavelets draw a special attention in this category. A commensurate procedure for constructing a superior M-band parametric wavelet system is proposed in this paper. The idea of modulation matrix decomposition and the relation with corresponding polyphase matrix and its factorization is exploited to possible extent to make the design process plain and easy. The appropriate polynomial matrix is put in place to extend the filter design to any required length. The simple property of the Kroneckor product of two matrices is contemplated to achieve M-band design. This paper ponders on the above-mentioned factors and accomplishes the task of designing an M-band parametric wavelet, which is complete in itself. Few examples are used to substantiate the proposed method.

关键词： Matrix decomposition Finite impulse response filter Wavelet analysis Frequency Computer networks Design engineering Electronic mail Signal processing Bandwidth Communications technology

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