Proceedings of 2011 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, 2011
In this paper, we propose an efficient method for long-term monitoring of a wide variety of marin... more In this paper, we propose an efficient method for long-term monitoring of a wide variety of marine mammals and human related activities using hydrophone data. The proposed method uses a combination of a two-stage denoising process followed by a new event detection function that estimates temporal predictability. The detection function utilizes long-term and shortterm predictions in order to detect various acoustic events from the background noise. The first stage of the denoising process uses temporal decomposition via Empirical Mode Decomposition to improve the correct detection rate, while the second stage uses Wavelet Packet spectral decomposition to reduce the false detection rate. Applied to event detection in NEPTUNE hydrophone recordings, the method demonstrates an accuracy of 95% and an F-measure of 94%.
Proceedings. IEEE International Conference on Multimedia and Expo
This paper proposes an efficient method of segmenting noisy audio signals using a linear binary W... more This paper proposes an efficient method of segmenting noisy audio signals using a linear binary Walsh transform, when the signal components are closely spaced and the time intervals between adjacent signal components are unknown. It is shown that the Walsh transform is appropriate for segmenting a noisy waveform. A subset of the Walsh functions is chosen to cover principally the
Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings., 2003
... barkat@ieee.org ... Moreover, in the proposed technique, a pseudo-noise (PN) sequence can be ... more ... barkat@ieee.org ... Moreover, in the proposed technique, a pseudo-noise (PN) sequence can be used as a secret key to modulate the water-mark signal, making the time-frequency signature harder to see or to modify, In the extraction process, not all pixels of the original image ...
This paper introduces a novel method to identify inspiratory and expiratory phases from single ch... more This paper introduces a novel method to identify inspiratory and expiratory phases from single channel tracheal breath sound (TBS) of different types, by proposing a new annotating index name as “mixing index ” (MI). An alignment scheme based on phase shift difference information has been firstly introduced to align the consecutive respiratory phase segments. MI is then proposed based on similarity measurements to annotate the respective inspiration/expiration in each aligned respiratory phase segment pair. By incorporating the novel alignment scheme, the presented index overcomes the problem of phase cancellation which affects the cross-coherence of the input segment pairs. As MI is invariant to spectral content and amplitude dynamics, the proposed method maintains a good performance even in the presence of adventitious sounds. A high averaged accuracy of 97.4% for adventitious sounds and 100 % for normal TBS have been thereby achieved. The proposed method has been a successful att...
This paper addresses blind source separation (BSS) problem of multiple speech signals in low sign... more This paper addresses blind source separation (BSS) problem of multiple speech signals in low signal-to-interference-noise ratio (SINR) environment. We consider an over-determined case so that we can form multiple sub-arrays (of which there are as many sensors as speech signals), and propose a novel hybrid scheme to obtain high fidelity speech signals after separation. Firstly, the proposed method applies the commonly-used BSS technique at each sub-array to separate the speech signals. Next, the outputs of the same speech signal from different sub-arrays are grouped to form a new subarray. We can then exploit the spatial diversity of the new sub-array to achieve high fidelity source separation. This configuration is the key innovation of this paper. Another contribution of the paper is on the justification of using the hybrid configuration to further increase the output SINR. From numerical analysis, it is demonstrated that 12 dB SINR improvement can be achieved using 5-element senso...
Article history: Received 12 January 2009 Accepted 18 June 2009 In this paper, we consider the pr... more Article history: Received 12 January 2009 Accepted 18 June 2009 In this paper, we consider the problem of heart sounds (HS) removal from respiratory sounds (RS), and a novel semi-blind single-channel source extraction algorithm is proposed. The proposed method is able to extract the underlying pure RS from the HS corrupted noisy input signals by incorporating the filter banks and template-based matching using FIR filters. For performance evaluation of the presented method, the average power spectral densities (PSD) of the input RS segments without HS have been compared with the PSD of the reconstructed signals over six selected frequency bands from 20 to 800Hz. The proposed method is tested for various types of RS recordings and found effective by yielding an overall maximum spectral difference of 2.8707 ± 0.9875dB for a frequency range below 800Hz.
Abstract In this paper, a new method for detecting events in noisy hydrophone data is developed. ... more Abstract In this paper, a new method for detecting events in noisy hydrophone data is developed. The method takes an image processing approach to the 1D hydrophone data by first converting it into a log-frequency spectrogram image (cepstrum). This image is then filtered by reconstructing it based on mutual information (MI) criteria of the dominant orientation map. The features of the reconstructed cepstrum are then enhanced using a combination of edge-tracking and noise smoothing. Binary feature classification on the processed cepstrum is performed using a least-squares support vector machine (LS-SVM). Compared to other methods, the proposed image-based event detection method exploits both the scale and the orientation information. The method showed that the detection performance in terms of binary classification sensitivity with more than 55% for rare events such as whale calls from noisy hydrophone recordings (a database size of over 160 h (1943 × 5 min) with a total of 39 events) from the NEPTUNE Canada project, with more than 99% specificity and 98% overall accuracy. With relatively low computational cost and high accuracy, the presented method is useful for automated long-term monitoring of a wide variety of marine mammals and human related activities from hydrophone data. The effectiveness of the proposed method is demonstrated over a large number of real noisy hydrophone recordings.
In Vehicular ad-hoc networks (VANETs), one of the challenging tasks is to find an accurate locali... more In Vehicular ad-hoc networks (VANETs), one of the challenging tasks is to find an accurate localization information. In this paper, we have addressed this problem by introducing a novel approach based on the idea of cooperative localization. Our proposed scheme incorporates different techniques of localization along with data fusion as well as vehicle-to-vehicle communication, to integrate the available data and cooperatively improve the accuracy of the localization information of the vehicles. The simulation results show that sharing the localization information and deploying that of the neighboring vehicles, not only assures the vehicles in a vicinity to obtain more accurate localization information, but also find the results robust to sensor inaccuracies or even to failures. Moreover, further improvement has been achieved by estimating the vehicle prior (prior mean and covariance) using unscented transform (UT) together with sequential decentralized extended Kalman filtering.
This article deals with the challenging problem of segmenting narrowly spaced cardiac events (S1 ... more This article deals with the challenging problem of segmenting narrowly spaced cardiac events (S1 and S2) in noisy phonocardiogram (PCG) signals by using a novel application of NMF based on time-scale approach. A novel energy-based method is proposed for the segmentation of noisy PCG signals in order to detect cardiac events, which could be closely spaced and separated by noisy gaps. The method is based on time-scale transform as well as nonnegative matrix factorization (NMF) and the segmentation problem is formulated using the paradigm of binary statistical hypothesis testing. The energy of the Morlet wavelet transform and NMF output is employed as a test statistics for segmentation where the number of scales are selected based on the preferences calculated along the time-scales. The simulation results using real recorded noisy PCG data that provide promising performance with high overall accuracy on the segmentation of narrowly separated, high noisy signals by our proposed method.
ABSTRACT The proposed VANET IR-CAS is a context aware system that utilizes information retrieval ... more ABSTRACT The proposed VANET IR-CAS is a context aware system that utilizes information retrieval (IR) techniques, such as indexing, document scoring and document similarity, to enhance context aware information dissemination in VANET. It uses a hybrid context model; spatial model for service filtering, ontology model for context reasoning and knowledge sharing, markup model for file exchange, and situational model for safety and convenience services. Its VANET OWL ontology managed by Jena semantic web framework succeeded in formalizing the semantics of VANET context domain and heightened the system abstraction level. Relevance of dispatched information to prospective recipients is enhanced by employing IR techniques and partial relevance. For commercial services, we used the hybrid vehicular communication (HVC) to increase the decentralized processing, exploit the vehicle processing power and increase user satisfaction and privacy. V2V is used for safety and convenience services where the level of abstraction has increased by using high level situation context attributes. In addition, more precise application notifications are now feasible after improving reasoning about situation certainty and severity. Hence, the main novelty of VANET IR-CAS is that it provides a highly abstract hybrid context model with IR based processing that raises the notification relevance, certainty and precision beside increasing decentralization and user satisfaction.
This paper aims to review on body sensor networks (BSNs) for sports from performance monitoring p... more This paper aims to review on body sensor networks (BSNs) for sports from performance monitoring point of view with some new thoughts. The focus of the paper is to show that wearable sensor is more efficient than cameras in measuring sport performance and thereby video data and video based systems can be replaced by wearable sensors. Here, the current state-of-the art in BSNs are mainly introduced relating to sports performance instead of physical activity and health/safety related issues for sports and to the best of our knowledge, this has not been done yet for different types of sports rather than a particular sport. Although the progress in BSN for sports performance is in early stage, the ultimate goal is to develop a complete training/match analysis tool using wearable sensors and various analyses techniques to monitor as well as improve performances in sports.
... Audio Engineering Society A Subband Domain Downmixing Scheme for Parametric Stereo Encoder Sa... more ... Audio Engineering Society A Subband Domain Downmixing Scheme for Parametric Stereo Encoder Samsudin , Evelyn Kurniawati , Farook Sattar , Ng ... Subjective listening test reveals that combination of PS and aacPlus [2], better known as enhanced aacPlus audio codec [3 ...
2004 International Conference on Image Processing 2004 Icip 04, Nov 24, 2004
This paper proposes a novel method for comer detection of gray level images using Gabor wavelets.... more This paper proposes a novel method for comer detection of gray level images using Gabor wavelets. Wavelet transform is a tool that can provide multi-scale analysis while analyzing the local behavior of a signal. Cahor wavelets are known for their good localization in the time-frequency plane. Furthermore, they provide the shape and orientation information of local structures directly. In the proposed algorithm. the input image is decomposed at several wavelet scales and along several directions. The magnitude along the direction that is orthogonal to the gradient orientation represents the "comemess" measurement. The proposed method is efficient since it has good localization. is robust to noise and achieves a high rate of true detection while keeping 3 low rate of false detection. Simulation results compare the proposed method with the two existing best approaches and show the good performance of the proposed method.
This paper presents a scheme that matches interest point features detected on two images taken fr... more This paper presents a scheme that matches interest point features detected on two images taken from different points of view. To accomplish this objective, we jointly consider the corner detection and matching problems. Firstly, a new multi-scale Plessey corner detector (MPCD) is used to detect the interest points. Secondly, the geometric constraint between two images is exploited, based on which we propose a new energy function that can approximate 2D affine transformation in a more efficient way. Only a small set of corners with the highest accuracy and robustness are considered in the first stage, consequently, a small data space is provided to the robust algorithm in the second stage reducing the computation time. Therefore, more information can be incorporated into our scheme based on corner detection and matching phases. We compare our method using the proposed MPCD with two standard corner detectors based on image matching. We also evaluate our proposed matching strategy against Zhengyou's method [Deriche, R., Zhang, Z., Luong, Q.-T., Faugeras, O., 1994. Robust recovery of the epipolar geometry for an uncalibrated stereo rig. In: European Conference on Computer Vision, Stockholm, Sweden, pp. 567-576]. Our scheme provides a new viewpoint and better results for the traditional feature matching problem.
Proceedings of 2011 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, 2011
In this paper, we propose an efficient method for long-term monitoring of a wide variety of marin... more In this paper, we propose an efficient method for long-term monitoring of a wide variety of marine mammals and human related activities using hydrophone data. The proposed method uses a combination of a two-stage denoising process followed by a new event detection function that estimates temporal predictability. The detection function utilizes long-term and shortterm predictions in order to detect various acoustic events from the background noise. The first stage of the denoising process uses temporal decomposition via Empirical Mode Decomposition to improve the correct detection rate, while the second stage uses Wavelet Packet spectral decomposition to reduce the false detection rate. Applied to event detection in NEPTUNE hydrophone recordings, the method demonstrates an accuracy of 95% and an F-measure of 94%.
Proceedings. IEEE International Conference on Multimedia and Expo
This paper proposes an efficient method of segmenting noisy audio signals using a linear binary W... more This paper proposes an efficient method of segmenting noisy audio signals using a linear binary Walsh transform, when the signal components are closely spaced and the time intervals between adjacent signal components are unknown. It is shown that the Walsh transform is appropriate for segmenting a noisy waveform. A subset of the Walsh functions is chosen to cover principally the
Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings., 2003
... barkat@ieee.org ... Moreover, in the proposed technique, a pseudo-noise (PN) sequence can be ... more ... barkat@ieee.org ... Moreover, in the proposed technique, a pseudo-noise (PN) sequence can be used as a secret key to modulate the water-mark signal, making the time-frequency signature harder to see or to modify, In the extraction process, not all pixels of the original image ...
This paper introduces a novel method to identify inspiratory and expiratory phases from single ch... more This paper introduces a novel method to identify inspiratory and expiratory phases from single channel tracheal breath sound (TBS) of different types, by proposing a new annotating index name as “mixing index ” (MI). An alignment scheme based on phase shift difference information has been firstly introduced to align the consecutive respiratory phase segments. MI is then proposed based on similarity measurements to annotate the respective inspiration/expiration in each aligned respiratory phase segment pair. By incorporating the novel alignment scheme, the presented index overcomes the problem of phase cancellation which affects the cross-coherence of the input segment pairs. As MI is invariant to spectral content and amplitude dynamics, the proposed method maintains a good performance even in the presence of adventitious sounds. A high averaged accuracy of 97.4% for adventitious sounds and 100 % for normal TBS have been thereby achieved. The proposed method has been a successful att...
This paper addresses blind source separation (BSS) problem of multiple speech signals in low sign... more This paper addresses blind source separation (BSS) problem of multiple speech signals in low signal-to-interference-noise ratio (SINR) environment. We consider an over-determined case so that we can form multiple sub-arrays (of which there are as many sensors as speech signals), and propose a novel hybrid scheme to obtain high fidelity speech signals after separation. Firstly, the proposed method applies the commonly-used BSS technique at each sub-array to separate the speech signals. Next, the outputs of the same speech signal from different sub-arrays are grouped to form a new subarray. We can then exploit the spatial diversity of the new sub-array to achieve high fidelity source separation. This configuration is the key innovation of this paper. Another contribution of the paper is on the justification of using the hybrid configuration to further increase the output SINR. From numerical analysis, it is demonstrated that 12 dB SINR improvement can be achieved using 5-element senso...
Article history: Received 12 January 2009 Accepted 18 June 2009 In this paper, we consider the pr... more Article history: Received 12 January 2009 Accepted 18 June 2009 In this paper, we consider the problem of heart sounds (HS) removal from respiratory sounds (RS), and a novel semi-blind single-channel source extraction algorithm is proposed. The proposed method is able to extract the underlying pure RS from the HS corrupted noisy input signals by incorporating the filter banks and template-based matching using FIR filters. For performance evaluation of the presented method, the average power spectral densities (PSD) of the input RS segments without HS have been compared with the PSD of the reconstructed signals over six selected frequency bands from 20 to 800Hz. The proposed method is tested for various types of RS recordings and found effective by yielding an overall maximum spectral difference of 2.8707 ± 0.9875dB for a frequency range below 800Hz.
Abstract In this paper, a new method for detecting events in noisy hydrophone data is developed. ... more Abstract In this paper, a new method for detecting events in noisy hydrophone data is developed. The method takes an image processing approach to the 1D hydrophone data by first converting it into a log-frequency spectrogram image (cepstrum). This image is then filtered by reconstructing it based on mutual information (MI) criteria of the dominant orientation map. The features of the reconstructed cepstrum are then enhanced using a combination of edge-tracking and noise smoothing. Binary feature classification on the processed cepstrum is performed using a least-squares support vector machine (LS-SVM). Compared to other methods, the proposed image-based event detection method exploits both the scale and the orientation information. The method showed that the detection performance in terms of binary classification sensitivity with more than 55% for rare events such as whale calls from noisy hydrophone recordings (a database size of over 160 h (1943 × 5 min) with a total of 39 events) from the NEPTUNE Canada project, with more than 99% specificity and 98% overall accuracy. With relatively low computational cost and high accuracy, the presented method is useful for automated long-term monitoring of a wide variety of marine mammals and human related activities from hydrophone data. The effectiveness of the proposed method is demonstrated over a large number of real noisy hydrophone recordings.
In Vehicular ad-hoc networks (VANETs), one of the challenging tasks is to find an accurate locali... more In Vehicular ad-hoc networks (VANETs), one of the challenging tasks is to find an accurate localization information. In this paper, we have addressed this problem by introducing a novel approach based on the idea of cooperative localization. Our proposed scheme incorporates different techniques of localization along with data fusion as well as vehicle-to-vehicle communication, to integrate the available data and cooperatively improve the accuracy of the localization information of the vehicles. The simulation results show that sharing the localization information and deploying that of the neighboring vehicles, not only assures the vehicles in a vicinity to obtain more accurate localization information, but also find the results robust to sensor inaccuracies or even to failures. Moreover, further improvement has been achieved by estimating the vehicle prior (prior mean and covariance) using unscented transform (UT) together with sequential decentralized extended Kalman filtering.
This article deals with the challenging problem of segmenting narrowly spaced cardiac events (S1 ... more This article deals with the challenging problem of segmenting narrowly spaced cardiac events (S1 and S2) in noisy phonocardiogram (PCG) signals by using a novel application of NMF based on time-scale approach. A novel energy-based method is proposed for the segmentation of noisy PCG signals in order to detect cardiac events, which could be closely spaced and separated by noisy gaps. The method is based on time-scale transform as well as nonnegative matrix factorization (NMF) and the segmentation problem is formulated using the paradigm of binary statistical hypothesis testing. The energy of the Morlet wavelet transform and NMF output is employed as a test statistics for segmentation where the number of scales are selected based on the preferences calculated along the time-scales. The simulation results using real recorded noisy PCG data that provide promising performance with high overall accuracy on the segmentation of narrowly separated, high noisy signals by our proposed method.
ABSTRACT The proposed VANET IR-CAS is a context aware system that utilizes information retrieval ... more ABSTRACT The proposed VANET IR-CAS is a context aware system that utilizes information retrieval (IR) techniques, such as indexing, document scoring and document similarity, to enhance context aware information dissemination in VANET. It uses a hybrid context model; spatial model for service filtering, ontology model for context reasoning and knowledge sharing, markup model for file exchange, and situational model for safety and convenience services. Its VANET OWL ontology managed by Jena semantic web framework succeeded in formalizing the semantics of VANET context domain and heightened the system abstraction level. Relevance of dispatched information to prospective recipients is enhanced by employing IR techniques and partial relevance. For commercial services, we used the hybrid vehicular communication (HVC) to increase the decentralized processing, exploit the vehicle processing power and increase user satisfaction and privacy. V2V is used for safety and convenience services where the level of abstraction has increased by using high level situation context attributes. In addition, more precise application notifications are now feasible after improving reasoning about situation certainty and severity. Hence, the main novelty of VANET IR-CAS is that it provides a highly abstract hybrid context model with IR based processing that raises the notification relevance, certainty and precision beside increasing decentralization and user satisfaction.
This paper aims to review on body sensor networks (BSNs) for sports from performance monitoring p... more This paper aims to review on body sensor networks (BSNs) for sports from performance monitoring point of view with some new thoughts. The focus of the paper is to show that wearable sensor is more efficient than cameras in measuring sport performance and thereby video data and video based systems can be replaced by wearable sensors. Here, the current state-of-the art in BSNs are mainly introduced relating to sports performance instead of physical activity and health/safety related issues for sports and to the best of our knowledge, this has not been done yet for different types of sports rather than a particular sport. Although the progress in BSN for sports performance is in early stage, the ultimate goal is to develop a complete training/match analysis tool using wearable sensors and various analyses techniques to monitor as well as improve performances in sports.
... Audio Engineering Society A Subband Domain Downmixing Scheme for Parametric Stereo Encoder Sa... more ... Audio Engineering Society A Subband Domain Downmixing Scheme for Parametric Stereo Encoder Samsudin , Evelyn Kurniawati , Farook Sattar , Ng ... Subjective listening test reveals that combination of PS and aacPlus [2], better known as enhanced aacPlus audio codec [3 ...
2004 International Conference on Image Processing 2004 Icip 04, Nov 24, 2004
This paper proposes a novel method for comer detection of gray level images using Gabor wavelets.... more This paper proposes a novel method for comer detection of gray level images using Gabor wavelets. Wavelet transform is a tool that can provide multi-scale analysis while analyzing the local behavior of a signal. Cahor wavelets are known for their good localization in the time-frequency plane. Furthermore, they provide the shape and orientation information of local structures directly. In the proposed algorithm. the input image is decomposed at several wavelet scales and along several directions. The magnitude along the direction that is orthogonal to the gradient orientation represents the "comemess" measurement. The proposed method is efficient since it has good localization. is robust to noise and achieves a high rate of true detection while keeping 3 low rate of false detection. Simulation results compare the proposed method with the two existing best approaches and show the good performance of the proposed method.
This paper presents a scheme that matches interest point features detected on two images taken fr... more This paper presents a scheme that matches interest point features detected on two images taken from different points of view. To accomplish this objective, we jointly consider the corner detection and matching problems. Firstly, a new multi-scale Plessey corner detector (MPCD) is used to detect the interest points. Secondly, the geometric constraint between two images is exploited, based on which we propose a new energy function that can approximate 2D affine transformation in a more efficient way. Only a small set of corners with the highest accuracy and robustness are considered in the first stage, consequently, a small data space is provided to the robust algorithm in the second stage reducing the computation time. Therefore, more information can be incorporated into our scheme based on corner detection and matching phases. We compare our method using the proposed MPCD with two standard corner detectors based on image matching. We also evaluate our proposed matching strategy against Zhengyou's method [Deriche, R., Zhang, Z., Luong, Q.-T., Faugeras, O., 1994. Robust recovery of the epipolar geometry for an uncalibrated stereo rig. In: European Conference on Computer Vision, Stockholm, Sweden, pp. 567-576]. Our scheme provides a new viewpoint and better results for the traditional feature matching problem.
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Papers by Farook Sattar