Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310498
C. Srinivasa, M. Bouchard, R. Pichevar, Hossein Najaf-Zadeh
A novel framework based on graph theory for structure discovery is applied to audio to find new types of audio objects which enable the compression of an input signal. It converts the sparse time-frequency representation of an audio signal into a graph by representing each data point as a vertex and the relationship between two vertices as an edge. Each edge is labelled based on a clustering algorithm which preserves a quality guarantee on the clusters. Frequent subgraphs are then extracted from this graph, via a mining algorithm, and recorded as objects. Tests performed using a corpus of audio excerpts show that the framework discovers new types of audio objects which yield an average compression gain of 23.53% while maintaining high audio quality.
{"title":"Graph theory for the discovery of non-parametric audio objects","authors":"C. Srinivasa, M. Bouchard, R. Pichevar, Hossein Najaf-Zadeh","doi":"10.1109/ISSPA.2012.6310498","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310498","url":null,"abstract":"A novel framework based on graph theory for structure discovery is applied to audio to find new types of audio objects which enable the compression of an input signal. It converts the sparse time-frequency representation of an audio signal into a graph by representing each data point as a vertex and the relationship between two vertices as an edge. Each edge is labelled based on a clustering algorithm which preserves a quality guarantee on the clusters. Frequent subgraphs are then extracted from this graph, via a mining algorithm, and recorded as objects. Tests performed using a corpus of audio excerpts show that the framework discovers new types of audio objects which yield an average compression gain of 23.53% while maintaining high audio quality.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128849754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310660
C. O’Reilly, R. Plamondon
This communication summarizes the outcome of our research program on the design of a diagnostic system for neuromuscular disorders based on the analysis of human movement using the Kinematic Theory of Rapid Human Movements. Herein, this design problem is split in sub-problems which are then described. The solutions adopted at each design step are explained. As an example of application, typical results obtained so far for the assessment of the most important modifiable risk factors of brain stroke (diabetes, hypertension, hypercholesterolemia, obesity, cardiac problems, and cigarette smoking) are reported by the means of the area under the receiver operating characteristic curve (AUC).
{"title":"Design of a neuromuscular disorders diagnostic system using human movement analysis","authors":"C. O’Reilly, R. Plamondon","doi":"10.1109/ISSPA.2012.6310660","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310660","url":null,"abstract":"This communication summarizes the outcome of our research program on the design of a diagnostic system for neuromuscular disorders based on the analysis of human movement using the Kinematic Theory of Rapid Human Movements. Herein, this design problem is split in sub-problems which are then described. The solutions adopted at each design step are explained. As an example of application, typical results obtained so far for the assessment of the most important modifiable risk factors of brain stroke (diabetes, hypertension, hypercholesterolemia, obesity, cardiac problems, and cigarette smoking) are reported by the means of the area under the receiver operating characteristic curve (AUC).","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"273 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121800623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310463
A. Sadhu, Bo Hu, S. Narasimhan
Wireless sensing technology has gained significant attention in the field of structural health monitoring (SHM). Various decentralized modal identification methods have been developed employing wireless sensors. However, one of themajor bottlenecks - especially dealing with long-term SHM - is the large volume of transmitted data. To overcome this problem, we present compressed sensing as a data reduction preprocessing tool within the framework of blind source separation. The results of source separation are ultimately used for modal identification of linear structures under ambient vibrations. When used together with sparsifying time-frequency decompositions, we show that accurate modal identification results are possible with high compression ratios. The main novelty in the method proposed here is in the application of compressive sensing for decentralized modal identification of civil structures.
{"title":"Blind source separation towards decentralized modal identification using compressive sampling","authors":"A. Sadhu, Bo Hu, S. Narasimhan","doi":"10.1109/ISSPA.2012.6310463","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310463","url":null,"abstract":"Wireless sensing technology has gained significant attention in the field of structural health monitoring (SHM). Various decentralized modal identification methods have been developed employing wireless sensors. However, one of themajor bottlenecks - especially dealing with long-term SHM - is the large volume of transmitted data. To overcome this problem, we present compressed sensing as a data reduction preprocessing tool within the framework of blind source separation. The results of source separation are ultimately used for modal identification of linear structures under ambient vibrations. When used together with sparsifying time-frequency decompositions, we show that accurate modal identification results are possible with high compression ratios. The main novelty in the method proposed here is in the application of compressive sensing for decentralized modal identification of civil structures.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121044197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310488
Qian Chen, Guyu Hu, Fang-lin Gu, Peng Xiang
The dynamic time warping (DTW) is a classic similarity measure which can handle the time warping issue in similarity computation of time series. And the DTW with constrained warping window is the most common and practical form of DTW. In this paper, the traditional learning method for optimal warping window of DTW is systematically analyzed. Then the time distance to measure the time deviation between two time series is introduced. Finally a new learning method for optimal warping window size based on DTW and time distance is proposed which can improve DTW classification accuracy with little additional computation. Experimental data show that the optimal DTW with best warping window get better classification accuracy when the new learning method is employed. Additionally, the classification accuracy is better than that of ERP and LCSS, and is close to that of TWED.
{"title":"Learning optimal warping window size of DTW for time series classification","authors":"Qian Chen, Guyu Hu, Fang-lin Gu, Peng Xiang","doi":"10.1109/ISSPA.2012.6310488","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310488","url":null,"abstract":"The dynamic time warping (DTW) is a classic similarity measure which can handle the time warping issue in similarity computation of time series. And the DTW with constrained warping window is the most common and practical form of DTW. In this paper, the traditional learning method for optimal warping window of DTW is systematically analyzed. Then the time distance to measure the time deviation between two time series is introduced. Finally a new learning method for optimal warping window size based on DTW and time distance is proposed which can improve DTW classification accuracy with little additional computation. Experimental data show that the optimal DTW with best warping window get better classification accuracy when the new learning method is employed. Additionally, the classification accuracy is better than that of ERP and LCSS, and is close to that of TWED.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121187727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310630
William C. Suski, Salil Banerjee, A. Hoover
Previous works in ultra-wideband (UWB) noise modeling have mostly focused on isolating the individual sources of error. However, it is important to recognize that some errors will always pass through to the system output. In this work, we methodically evaluated the system-level noise of a UWB position tracking system. We define system-level noise as the measurement error obtained when the system is installed in a real-world environment. Our results show that a multi-modal noise model will be essential for filtering system-level noise. To encourage further research, all of our data has been made publicly available.
{"title":"System-level noise of an ultra-wideband tracking system","authors":"William C. Suski, Salil Banerjee, A. Hoover","doi":"10.1109/ISSPA.2012.6310630","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310630","url":null,"abstract":"Previous works in ultra-wideband (UWB) noise modeling have mostly focused on isolating the individual sources of error. However, it is important to recognize that some errors will always pass through to the system output. In this work, we methodically evaluated the system-level noise of a UWB position tracking system. We define system-level noise as the measurement error obtained when the system is installed in a real-world environment. Our results show that a multi-modal noise model will be essential for filtering system-level noise. To encourage further research, all of our data has been made publicly available.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121235039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310699
A. Sengodan, W. Cockshott
The main challenge of ground penetrating radar (GPR) based land mine detection is to have an accurate image analysis method that is capable of reducing false alarms. However an accurate image relies on having sufficient spatial resolution in the received signal. But because the diameter of an AP mine can be as low as 2cm and many soils have very high attenuations at frequencies above 3GHz, the accurate detection of landmines is accomplished using advanced algorithms. Using image reconstruction and by carrying out the system level analysis of the issues involved with recognition of landmines allows the landmine detection problem to be solved. The SIMCA ('SIMulated Correlation Algorithm') is a novel and accurate landmine detection tool that carries out correlation between a simulated GPR trace and a clutter1 removed original GPR trace. This correlation is performed using the MATLAB® processing environment. The authors tried using convolution and correlation. But in this paper the correlated results are presented because they produced better results. Validation of the results from the algorithm was done by an expert GPR user and 4 other general users who predict the location of landmines. These predicted results are compared with the ground truth data.
{"title":"The SIMCA algorithm for processing ground penetrating radar data and its use in landmine detection","authors":"A. Sengodan, W. Cockshott","doi":"10.1109/ISSPA.2012.6310699","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310699","url":null,"abstract":"The main challenge of ground penetrating radar (GPR) based land mine detection is to have an accurate image analysis method that is capable of reducing false alarms. However an accurate image relies on having sufficient spatial resolution in the received signal. But because the diameter of an AP mine can be as low as 2cm and many soils have very high attenuations at frequencies above 3GHz, the accurate detection of landmines is accomplished using advanced algorithms. Using image reconstruction and by carrying out the system level analysis of the issues involved with recognition of landmines allows the landmine detection problem to be solved. The SIMCA ('SIMulated Correlation Algorithm') is a novel and accurate landmine detection tool that carries out correlation between a simulated GPR trace and a clutter1 removed original GPR trace. This correlation is performed using the MATLAB® processing environment. The authors tried using convolution and correlation. But in this paper the correlated results are presented because they produced better results. Validation of the results from the algorithm was done by an expert GPR user and 4 other general users who predict the location of landmines. These predicted results are compared with the ground truth data.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116512175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310596
Messaoud Bengherabi, F. Harizi, A. Guessoum, M. Cheriet
The aim of this paper is to investigate the user-specific two-level fusion strategy in the context of multimodal biometrics. In this strategy, a client-specific score normalization procedure is applied firstly to each of the system outputs to be fused. Then, the resulting normalized outputs are fed into a common classifier. The logistic regression, non-confidence weighted sum and the likelihood ratio based on Gaussian mixture model are used as back-end classifiers. Three client-specific score normalization procedures are considered in this paper, i.e. Z-norm, F-norm and the Model-Specific Log-Likelihood Ratio MSLLR-norm. Our first findings based on 15 fusion experiments on the XM2VTS score database show that when the previous two-level fusion strategy is applied, the resulting fusion classifier outperforms the baseline classifiers significantly and a relative reduction of more than 50% in the equal error rate can be achieved. The second finding is that when using this two-level user-specific fusion strategy, the design of the final classifier is simplified and performance generalization of baseline classifiers is not straightforward. A great attention must be given to the choice of the combination normalization-back-end classifier.
{"title":"Incorporating user specific normalization in multimodal biometric fusion system","authors":"Messaoud Bengherabi, F. Harizi, A. Guessoum, M. Cheriet","doi":"10.1109/ISSPA.2012.6310596","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310596","url":null,"abstract":"The aim of this paper is to investigate the user-specific two-level fusion strategy in the context of multimodal biometrics. In this strategy, a client-specific score normalization procedure is applied firstly to each of the system outputs to be fused. Then, the resulting normalized outputs are fed into a common classifier. The logistic regression, non-confidence weighted sum and the likelihood ratio based on Gaussian mixture model are used as back-end classifiers. Three client-specific score normalization procedures are considered in this paper, i.e. Z-norm, F-norm and the Model-Specific Log-Likelihood Ratio MSLLR-norm. Our first findings based on 15 fusion experiments on the XM2VTS score database show that when the previous two-level fusion strategy is applied, the resulting fusion classifier outperforms the baseline classifiers significantly and a relative reduction of more than 50% in the equal error rate can be achieved. The second finding is that when using this two-level user-specific fusion strategy, the design of the final classifier is simplified and performance generalization of baseline classifiers is not straightforward. A great attention must be given to the choice of the combination normalization-back-end classifier.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126497544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310608
Isaac Nickaein, M. Rahmati, S. S. Ghidary, A. Zohrabi
Distributed Video Coding (DVC) is a new class of video coding techniques with the aim of coding the decentralized video sources. While the Stanford Wyner-Ziv codec is a well-known architecture in DVC literature, one of its main drawbacks is the presence of a feedback channel from the decoder to the encoder. This feedback channel makes the use of the codec impractical in some applications. Since the only application of the feedback channel is in requesting more parity bits from the encoder, it could be omitted if the encoder estimates the required parity bits and sends them at once. In this paper, a new method of bitrate estimation using a neural network trained by a new set of features is proposed. In addition, a Hybrid mode is proposed that reduces computational complexity at the decoder in a conventional Wyner-Ziv codec.
{"title":"Feedback-free and hybrid distributed video coding using neural networks","authors":"Isaac Nickaein, M. Rahmati, S. S. Ghidary, A. Zohrabi","doi":"10.1109/ISSPA.2012.6310608","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310608","url":null,"abstract":"Distributed Video Coding (DVC) is a new class of video coding techniques with the aim of coding the decentralized video sources. While the Stanford Wyner-Ziv codec is a well-known architecture in DVC literature, one of its main drawbacks is the presence of a feedback channel from the decoder to the encoder. This feedback channel makes the use of the codec impractical in some applications. Since the only application of the feedback channel is in requesting more parity bits from the encoder, it could be omitted if the encoder estimates the required parity bits and sends them at once. In this paper, a new method of bitrate estimation using a neural network trained by a new set of features is proposed. In addition, a Hybrid mode is proposed that reduces computational complexity at the decoder in a conventional Wyner-Ziv codec.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134002834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310471
S. Impedovo, Francesco Maurizio Mangini, G. Pirlo
In this paper a new clustering technique for improving off-line handwritten digit recognition is introduced. Clustering design is approached as an optimization problem in which the objective function to be minimized is the cost function associated to the classification, that is here performed by the k-nearest neighbor (k-NN) classifier based on the Sokal and Michener dissimilarity measure. For this purpose, a genetic algorithm is used to determine the best cluster centers to reduce classification time, without suffering a great loss in accuracy. In addition, an effective strategy for generating the initial-population of the genetic algorithm is also presented. The experimental tests carried out using the MNIST database show the effectiveness of this method.
{"title":"A genetic algorithm based clustering approach for improving off-line handwritten digit classification","authors":"S. Impedovo, Francesco Maurizio Mangini, G. Pirlo","doi":"10.1109/ISSPA.2012.6310471","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310471","url":null,"abstract":"In this paper a new clustering technique for improving off-line handwritten digit recognition is introduced. Clustering design is approached as an optimization problem in which the objective function to be minimized is the cost function associated to the classification, that is here performed by the k-nearest neighbor (k-NN) classifier based on the Sokal and Michener dissimilarity measure. For this purpose, a genetic algorithm is used to determine the best cluster centers to reduce classification time, without suffering a great loss in accuracy. In addition, an effective strategy for generating the initial-population of the genetic algorithm is also presented. The experimental tests carried out using the MNIST database show the effectiveness of this method.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130639213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-07-02DOI: 10.1109/ISSPA.2012.6310665
R. Hedjam, M. Cheriet
In this paper we present a new method for hyperspectral band selection problem. The principle is to create a band adjacency graph (BAG) where the nodes represent the bands and the edges represent the similarity weights between the bands. The Markov Clustering Process (abbreviated MCL process) defines a sequence of stochastic matrices by alternation of two operators on the associated affinity matrix to form distinct clusters of high correlated bands. Each cluster is represented by one band and the representative bands will form the new data cube to be used in subsequent processing. The proposed algorithm is tested on a real dataset and compared against state-of-art. The results are promising.
{"title":"Hyperspectral band selection based on graph clustering","authors":"R. Hedjam, M. Cheriet","doi":"10.1109/ISSPA.2012.6310665","DOIUrl":"https://doi.org/10.1109/ISSPA.2012.6310665","url":null,"abstract":"In this paper we present a new method for hyperspectral band selection problem. The principle is to create a band adjacency graph (BAG) where the nodes represent the bands and the edges represent the similarity weights between the bands. The Markov Clustering Process (abbreviated MCL process) defines a sequence of stochastic matrices by alternation of two operators on the associated affinity matrix to form distinct clusters of high correlated bands. Each cluster is represented by one band and the representative bands will form the new data cube to be used in subsequent processing. The proposed algorithm is tested on a real dataset and compared against state-of-art. The results are promising.","PeriodicalId":248763,"journal":{"name":"2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116931776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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