Omar Farooq
Aligarh Muslim University, Electronics Engg., Faculty Member
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Research Interests: Computer Science, Epilepsy, Channel Coding, EEG, Electroencephalography, and 14 moreMultichannel, Channel Estimation, EEG Signal Processing, Radiation Detectors, Kurtosis, Skewness, Latency, Antiepileptic drugs, Embedded Systems Education and Applications, Latency Reduction, False Alarm Eliminaation in Intrusion Detection System, Normalized coefficient of variation (NCOV), ncov, and epoch window
ABSTRACT: In this paper, an image encryption algorithm based on chaos and discrete wavelet transform is proposed. The plain-image is first transformed to wavelet domain and low frequency band is decomposed into nonoverlapping blocks of... more
ABSTRACT: In this paper, an image encryption algorithm based on chaos and discrete wavelet transform is proposed. The plain-image is first transformed to wavelet domain and low frequency band is decomposed into nonoverlapping blocks of DWT coefficients. A novel Block-Based Scrambling (BBS) using 2D Cat Map is performed in DWT domain. BBS scrambling is implemented by considering with a large block size and the blocks size is gets reduced iteratively at each level of scrambling. The scrambling of blocks is performed at ...
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A telemedicine system is described for monitoring vital signs and general health indicators of patients with cardiac and diabetic conditions. Telemetry from wireless sensors and readings from other instruments are combined into a... more
A telemedicine system is described for monitoring vital signs and general health indicators of patients with cardiac and diabetic conditions. Telemetry from wireless sensors and readings from other instruments are combined into a comprehensive set of measured patient parameters. Using a combination of mobile device applications and web browser, the data can be stored, accessed, and displayed using mobile internet communications to the central server. As an extra layer of security in the data transmission, information embedded in the data is used in its verification. The paper highlights features that could be enhanced from previous systems by using alternative components or methods.
A telemedicine system is described for monitoring vital signs and general health indicators of patients with cardiac and diabetic conditions. Telemetry from wireless sensors and readings from other instruments are combined into a... more
A telemedicine system is described for monitoring vital signs and general health indicators of patients with cardiac and diabetic conditions. Telemetry from wireless sensors and readings from other instruments are combined into a comprehensive set of measured patient parameters. Using a combination of mobile device applications and web browser, the data can be stored, accessed, and displayed using mobile internet communications to the central server. As an extra layer of security in the data transmission, information embedded in the data is used in its verification. The paper highlights features that could be enhanced from previous systems by using alternative components or methods.
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Low-cost high-quality electrocardiographic diagnosis systems, Body Area Sensor Networks (BASNs) have become important for healthcare service providers but security and integrity of medical signal are not widely researched. This paper... more
Low-cost high-quality electrocardiographic diagnosis systems, Body Area Sensor Networks (BASNs) have become important for healthcare service providers but security and integrity of medical signal are not widely researched. This paper proposes a simple and novel partial encryption for the security of electrocardiographic data. The scheme is designed and developed on a configurable FPGA device and uses only half of the ECG data for encryption. Since the computation is done on reduced data, the computation cost is decreased and the processing speed of encryption process is augmented. The proposed hardware was implemented on Xilinx Virtex4 and Spartan3 FPGA giving maximum clock frequency of 286.8 MHz and 139.5 MHz respectively. The encrypted data along with the remaining unencrypted part of the data are used to construct the encrypted electrocardiographic signal giving it a noise like characteristics. This makes the encrypted signals uncorrelated to original ECG giving an average cross-correlation of –0.00024. Reference to this paper should be made as follows: Izharuddin, Farooq, O. and Rafiq, M.Q. (2015) 'Partial encryption of ECG with reduced complexity and its FPGA implementation', Int. Chairman in 1997. He is an expert member of NBA committee, selection committee to various universities in India, academic council of different universities and resource person to different places for delivering expert lectures. He has guided five research scholars for PhD and three are under his supervision. He has published many papers in reputed journals/conferences, like
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Abstract The area of speech recognition has been thoroughly researched during the past fifty years; however, robustness is still an important challenge to overcome. It has been established that there exists a correlation between speech... more
Abstract The area of speech recognition has been thoroughly researched during the past fifty years; however, robustness is still an important challenge to overcome. It has been established that there exists a correlation between speech produced and lip motion which is helpful in the adverse background conditions to improve the recognition performance. This chapter presents main components used in audio-visual speech recognition systems. Results of a prototype experiment conducted on audio-visual corpora for Hindi speech ...
Résumé/Abstract In this paper a brief overview of digital watermarking is given and a wavelet based fragile image watermarking scheme is proposed. For detection of tampering in an image, a Tamper Assessment Function (TAF) is evaluated and... more
Résumé/Abstract In this paper a brief overview of digital watermarking is given and a wavelet based fragile image watermarking scheme is proposed. For detection of tampering in an image, a Tamper Assessment Function (TAF) is evaluated and compared to a threshold. The watermark is embedded at different level of wavelet decomposition and attacks based on average filtering and JPEG compression with different compression ratios have been tested. The results show that the tampering can be detected by choosing the ...
Résumé/Abstract In this paper new wavelet features are proposed for speaker-independent phoneme recognition. These new features are found to overcome the problem of shift in the signal as reported for the earlier features obtained by... more
Résumé/Abstract In this paper new wavelet features are proposed for speaker-independent phoneme recognition. These new features are found to overcome the problem of shift in the signal as reported for the earlier features obtained by wavelet transform. These features have been extracted from the phonemes obtained from the TIMIT database. The Linear Discriminant Analysis (LDA) method was used for the purpose of training and testing the classification of phonemes based on these features. No common speakers were chosen ...
Summary This paper presents the use of discrete wavelet transform for feature extraction of phoneme. Instead of using the conventional wavelet coefficients, energy per sample is calculated in different frequency bands and used as... more
Summary This paper presents the use of discrete wavelet transform for feature extraction of phoneme. Instead of using the conventional wavelet coefficients, energy per sample is calculated in different frequency bands and used as features. Training and test samples of the phonemes were obtained from the TIMIT database from the dialect region DR1 and DR2. Features extracted were updated every 8ms to account for the non-stationary property of the speech signal. For the classification of the phonemes two different classifiers were used ...
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Abstract: In this paper a modified function for wavelet-based denoising scheme is proposed and tested for speaker independent noisy Hindi digits recognition using Mel-Frequency Cepstral Coefficients (MFCC) features. Recognition... more
Abstract: In this paper a modified function for wavelet-based denoising scheme is proposed and tested for speaker independent noisy Hindi digits recognition using Mel-Frequency Cepstral Coefficients (MFCC) features. Recognition performance achieved by using the proposed scheme is found to be superior to hard/soft threshold using one and two level denoising in the Signalto-Noise Ratio (SNR) range of 30 dB to–5 dB. Proposed denoising scheme helps in improving the recognition performance over the entire SNR range under ...
This paper investigates effectiveness of using a non-invasive Electroencephalographic (EEG) activity for Brain Computer Interface, to analyze the brain activity and translate human elbow movement into the movement of an artificial... more
This paper investigates effectiveness of using a non-invasive Electroencephalographic (EEG) activity for Brain Computer Interface, to analyze the brain activity and translate human elbow movement into the movement of an artificial actuator. Simple time domain statistical features (mean, variance, skewness, kurtosis, energy, inter quartile range and median absolute deviation) are extracted to detect left to right and right to left elbow movement by using a linear discriminant function based classifier. A robotic arm is used to mimic human elbow movement and its movement was controlled by the classifier's output. An overall accuracy of 73% is achieved in the classifications of two elbow movement using EEG signal.
The aim of the study is to investigate best features for the classification of pronation and extension of wrist movements ,10-20 international montage was used for the recordings of EEG data on 16 channels.Data was processed ,filtered and... more
The aim of the study is to investigate best features for the classification of pronation and extension of wrist movements ,10-20 international montage was used for the recordings of EEG data on 16 channels.Data was processed ,filtered and windowed.Histogram plots were used for selection of features ,standard statistical features were employed in the investigation and the result suggest they provide discriminatory conditions .While the scope and depth of the study was limited,the result do suggest variance,skewness and kurtosis can be used for designing the classifier for both the movements.
The aim of our study is to investigate best features for the classification of pronation and extension of wrist movements and further use the best possible classifier to achieve accurate classification of movements. 10-20 International... more
The aim of our study is to investigate best features for the classification of pronation and extension of wrist movements and further use the best possible classifier to achieve accurate classification of movements. 10-20 International Montage was used for the recording of EEG data on 16 channels. Data was processed, filtered and windowed. Histogram plots were used for selection of features. Standard statistical features were employed in the investigation and the result suggests that they provide discriminatory conditions. While the scope and depth of the study was limited, the results do suggest that variance, mean, skewness and kurtosis can be used for designing the classifier for both the movements. Different Standard classifiers are finally designed and trained to distinguish between different motor movements. I. INTRODUCTION A brain-computer interface (BCI) is a system which translates a subject's intentions into a control signal for a device, e.g., a computer application, ...
ABSTRACT Multi-stage scheduling has been proposed as a hierarchical scheduling technique to achieve load balancing in massively parallel multiprocessor networks. Existing hierarchical approaches can not easily map on multiprocessor system... more
ABSTRACT Multi-stage scheduling has been proposed as a hierarchical scheduling technique to achieve load balancing in massively parallel multiprocessor networks. Existing hierarchical approaches can not easily map on multiprocessor system because they do not incorporate the inherent parallelism of a multiprocessor system when task allocation is made. In this paper a hierarchical based novel scheduling scheme named as Multi-stage scheduling has been proposed and implemented on multiprocessor systems. The scheme divides the whole network into various segments, where each segment consists of a set of processors and makes the load balancing in an incremental way. The performance of the proposed scheme is evaluated and a comparison with the existing scheme is made. The load imbalance on a particular multiprocessor system is calculated in terms of Load Imbalance Factor (LIF). Simulation results shows that the proposed multi-stage scheduling gives better performance in terms of task scheduling on different multiprocessor interconnection networks.
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Abstract: This article evaluates robustness of admissible wavelet packet based features for continuous speech recognition. The recognition accuracy is compared with the standard mel frequency cepstral coefficients (MFCC) under clean and... more
Abstract: This article evaluates robustness of admissible wavelet packet based features for continuous speech recognition. The recognition accuracy is compared with the standard mel frequency cepstral coefficients (MFCC) under clean and noisy environment. This is carried out by adding white Gaussian and speech noise to the phonemes of the TIMIT database to generate different levels of signal to noise ratio. Further, a wavelet based denoising technique is proposed as a front-end for noise reduction. Soft and hard thresholding ...
Research Interests: Phonetics, Pattern Recognition, Modeling, User Interface, Automatic Speech Recognition, and 19 moreSpeech Recognition, Hidden Markov Models, Word Recognition, Wavelet Transform, Wavelet Transforms, Noise reduction, Natural language, hidden Markov model, Word, Feature Extraction, Hmm, Cepstrum, Robustness, Gaussian noise, Signal to Noise Ratio, White Noise, Database, Continuous Speech Recognition, and Markov model
In this paper, an image scrambling technique based on chaotic systems is proposed. Scrambling is performed in transform domain to overcome the drawbacks of spatial domain scrambling. The transformed image is first decomposed into blocks... more
In this paper, an image scrambling technique based on chaotic systems is proposed. Scrambling is performed in transform domain to overcome the drawbacks of spatial domain scrambling. The transformed image is first decomposed into blocks of coefficients which are scrambled using 2D chaotic map; this process is repeated for various levels. At each level, the control parameters of scrambling are randomly generated through another 2D chaotic system to make the process of scrambling key-dependent. Experimental analyses show that the technique is efficient and provides good scrambling effect, high security with less computation. It is also shown that discrete wavelet transform implementation has better performance than discrete cosine transform for a noisy transmission channel.
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Speech recognition by machine is crucial ingredients for many important applications of human-machine interface. The combination of audio and visual information promises higher recognition accuracy and robustness in comparison to audio... more
Speech recognition by machine is crucial ingredients for many important applications of human-machine interface. The combination of audio and visual information promises higher recognition accuracy and robustness in comparison to audio information only. This paper gives an overview of different approaches used for speech recognition. This paper helps in choosing the technique along with their relative merits & demerits for audio visual speech recognition. This paper concludes with the decision of developing technique to increase the accuracy of audio visual recognition system in the noisy background conditions.
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Many applications based on satellite communication like national defence and security rely on the satellite images as an important source of information. It is therefore, mandatory to secure satellite imagery while transmitting them over... more
Many applications based on satellite communication like national defence and security rely on the satellite images as an important source of information. It is therefore, mandatory to secure satellite imagery while transmitting them over communication channels to protect ...
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ABSTRACT Balancing the computational load over multiprocessor networks is an important problem in massively parallel systems. The key advantage of such systems is to allow concurrent execution of workload characterized by computation... more
ABSTRACT Balancing the computational load over multiprocessor networks is an important problem in massively parallel systems. The key advantage of such systems is to allow concurrent execution of workload characterized by computation units known as processes or tasks. The scheduling problem is to maintain a balanced execution of all the tasks among the various available processors (nodes) in a multiprocessor network. This paper studies the scheduling of tasks on a pool of identical nodes which are connected through some interconnection network. A novel dynamic scheduling scheme named as Two Round Scheduling (TRS) scheme has been proposed and implemented for scheduling the load on various multiprocessor interconnection networks. In particular, the performance of the proposed scheme is evaluated for linearly extensible multiprocessor systems, however, a comparison is also made with other standard existing multiprocessor systems. The TRS operates in two steps to make the network fully balanced. The performance of this scheme is evaluated in terms of the performance index called Load Imbalance Factor (LIF), which represents the deviation of load among processors and the balancing time for different types of loads. The comparative simulation study shows that the proposed TRS scheme gives better performance in terms of task scheduling on various linearly extensible multiprocessor networks for both uniform and non-uniform types of loads.
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Abstract: One of the most troubling features of epileptic seizure is its apparently erratic nature. Researches point to some changes in dynamical properties of electroencephalogram (EEG) indicative of epileptic seizures. If these changes... more
Abstract: One of the most troubling features of epileptic seizure is its apparently erratic nature. Researches point to some changes in dynamical properties of electroencephalogram (EEG) indicative of epileptic seizures. If these changes could be properly detected, they could be used to predict seizures. Prior knowledge regarding an oncoming seizure can be used to actuate some intervention mechanism to prevent or control seizure. A method of automatic seizure prediction using wavelet entropy (WE) and mean ...
This paper presents identification of 4 different wrist movements by analyzing fore-arm surface Electromyogram (sEMG) signals. In order to reduce noise picked up during the recording, wavelet based denoising is applied using Daubechies... more
This paper presents identification of 4 different wrist movements by analyzing fore-arm surface Electromyogram (sEMG) signals. In order to reduce noise picked up during the recording, wavelet based denoising is applied using Daubechies mother wavelet. Spectral features along with Wilson's amplitude were extracted and given to a linear classifier. The experimental result shows better recognition performance using the given features when denoising is applied. The maximum accuracy for identification of four wrist movement was 97.5% which is quite significant as compared to the previous researches.
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The detection of nonconvulsive seizures (NCSz) is a challenge because of the lack of physical symptoms, which may delay the diagnosis of the disease. Many researchers have reported automatic detection of seizures. However, few... more
The detection of nonconvulsive seizures (NCSz) is a challenge because of the lack of physical symptoms, which may delay the diagnosis of the disease. Many researchers have reported automatic detection of seizures. However, few investigators have concentrated on detection of NCSz. This article proposes a method for reliable detection of NCSz. The electroencephalography (EEG) signal is usually contaminated by various nonstationary noises. Signal denoising is an important preprocessing step in the analysis of such signals. In this study, a new wavelet-based denoising approach using cubical thresholding has been proposed to reduce noise from the EEG signal prior to analysis. Three statistical features were extracted from wavelet frequency bands, encompassing the frequency range of 0 to 8, 8 to 16, 16 to 32, and 0 to 32 Hz. Extracted features were used to train linear classifier to discriminate between normal and seizure EEGs. The performance of the method was tested on a database of nin...
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Epilepsy is a physical condition that occurs when there is a sudden, brief change in the normal working of brain. At this time, the brain cells are unable to function properly and the level of consciousness, movement etc. may get... more
Epilepsy is a physical condition that occurs when there is a sudden, brief change in the normal working of brain. At this time, the brain cells are unable to function properly and the level of consciousness, movement etc. may get affected. These physical changes occur due to the hyper-synchronous firing of neurons within the brain. Most of the existing methods to analyze epilepsy depend on visual inspection of EEG recording of patients by experts who are very small in number. Also this method takes more time in diagnosis of epilepsy since ...
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ABSTRACT This paper proposes an algorithm for the detection of non-convulsive seizures (NCSz), based on the Autoregressive (AR) modeling of EEG over the frequency band of 0-31 Hz. Simple linear classifier was used for the classification... more
ABSTRACT This paper proposes an algorithm for the detection of non-convulsive seizures (NCSz), based on the Autoregressive (AR) modeling of EEG over the frequency band of 0-31 Hz. Simple linear classifier was used for the classification between the normal and seizure EEG. The algorithm was tested on the scalp EEG database of 5 patients, collected at All India Institute of Medical Sciences (AIIMS), New Delhi. The database consists of 13 seizures of different duration. The results were reported for 11 seizures. Overall sensitivity and specificity achieved by the method was 86.8% and 96.9% respectively.
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