Pub Date : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369547
T. Ghirmai
When a Markov Chain Monte Carlo (MCMC) method is applied to solve signal-processing problems, it is commonly implemented using Gibbs sampler. The implementation of Gibbs sampler requires the availability of full conditional probability density functions (pdfs) of all the parameters of interest of a problem. For some problems, however, the full conditional pdfs of all the parameters of interest are not readily available. In such cases, Metropolis-Hastings method can be incorporated within a Gibbs sampler to draw samples from the parameters whose full conditional pdf cannot be analytically determined. This paper demonstrates the application of such an algorithm, known as Metropolis-Hastings-within Gibbs, by considering the problem of joint data detection and channel estimation of a single-hop relay-based communication system. By formulating the signal model of the transmission process in alternative ways, we develop two algorithms for the problem. Moreover, simulation results of the two algorithms are provided to illustrate their effectiveness.
{"title":"Applying Metropolis-Hastings-within-Gibbs algorithms for data detection in relay-based communication systems","authors":"T. Ghirmai","doi":"10.1109/DSP-SPE.2015.7369547","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369547","url":null,"abstract":"When a Markov Chain Monte Carlo (MCMC) method is applied to solve signal-processing problems, it is commonly implemented using Gibbs sampler. The implementation of Gibbs sampler requires the availability of full conditional probability density functions (pdfs) of all the parameters of interest of a problem. For some problems, however, the full conditional pdfs of all the parameters of interest are not readily available. In such cases, Metropolis-Hastings method can be incorporated within a Gibbs sampler to draw samples from the parameters whose full conditional pdf cannot be analytically determined. This paper demonstrates the application of such an algorithm, known as Metropolis-Hastings-within Gibbs, by considering the problem of joint data detection and channel estimation of a single-hop relay-based communication system. By formulating the signal model of the transmission process in alternative ways, we develop two algorithms for the problem. Moreover, simulation results of the two algorithms are provided to illustrate their effectiveness.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"72 1","pages":"167-171"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86874686","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369572
N. Kehtarnavaz, Shane Parris, Abhishek Sehgal
This paper presents a newly developed laboratory paradigm for teaching applied or real-time digital signal processing courses. It involves the utilization of smartphones to implement digital signal processing algorithms in real-time using ARM processors of smartphones. Representative laboratory experiments together with an application project running on smartphones as apps are discussed in the paper. It is shown that such a paradigm provides a cost-free and a truly mobile laboratory environment for students to learn implementation aspects of signal processing algorithms.
{"title":"Using smartphones as mobile implementation platforms for applied digital signal processing courses","authors":"N. Kehtarnavaz, Shane Parris, Abhishek Sehgal","doi":"10.1109/DSP-SPE.2015.7369572","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369572","url":null,"abstract":"This paper presents a newly developed laboratory paradigm for teaching applied or real-time digital signal processing courses. It involves the utilization of smartphones to implement digital signal processing algorithms in real-time using ARM processors of smartphones. Representative laboratory experiments together with an application project running on smartphones as apps are discussed in the paper. It is shown that such a paradigm provides a cost-free and a truly mobile laboratory environment for students to learn implementation aspects of signal processing algorithms.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"90 1","pages":"313-318"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89379050","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369563
R. Black, B. Jeffs, K. Warnick, G. Hellbourg, A. Chippendale
The ASKAP radio telescope in Australia is the first synthesis imaging array to use phased-array feeds (PAFs). These permit wider fields of view and new modalities for radio-frequency interference (RFI) mitigation. Previous work on imaging-array RFI cancellation has assumed that processing bandwidths are very narrow, and correlator integration times are short. However, these assumptions do not necessarily reflect real-world instrument limitations. This paper explores adaptive array cancellation algorithm effectiveness on ASKAP for realistic bandwidths and integration times. With ASKAP's beamforming PAFs on each dish, followed by a central correlation processor across beamformed signals from all dishes, one may consider algorithms that span multiple levels in the hierarchical signal processing chain. We compare performance for several subspace-projection-based algorithms applied to different tiers of this extended architecture. Simulation results demonstrate that it is most effective to cancel at the PAF beamformers.
{"title":"Multi-tier interference-cancelling array processing for the ASKAP radio telescope","authors":"R. Black, B. Jeffs, K. Warnick, G. Hellbourg, A. Chippendale","doi":"10.1109/DSP-SPE.2015.7369563","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369563","url":null,"abstract":"The ASKAP radio telescope in Australia is the first synthesis imaging array to use phased-array feeds (PAFs). These permit wider fields of view and new modalities for radio-frequency interference (RFI) mitigation. Previous work on imaging-array RFI cancellation has assumed that processing bandwidths are very narrow, and correlator integration times are short. However, these assumptions do not necessarily reflect real-world instrument limitations. This paper explores adaptive array cancellation algorithm effectiveness on ASKAP for realistic bandwidths and integration times. With ASKAP's beamforming PAFs on each dish, followed by a central correlation processor across beamformed signals from all dishes, one may consider algorithms that span multiple levels in the hierarchical signal processing chain. We compare performance for several subspace-projection-based algorithms applied to different tiers of this extended architecture. Simulation results demonstrate that it is most effective to cancel at the PAF beamformers.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"16 1","pages":"261-266"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89383646","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369534
Hao Chen, Tsang-Yi Wang
Distributed detection with dependent observations is always a challenging problem. The problem of detection with shared information has many applications when sensors have overlapped measurements, e.g., when distributed detection is performed in a security system where sensors have overlapped coverages. For this shared information scenario, we investigate the distributed detection problem in parallel fusion networks. The design problem is how to best utilize the common information at both the local sensors and the fusion center to achieve best possible performance. We derive the necessary condition for the optimal sensor decision rules for all sensors. In addition, we investigate the system performance by comparing the optimal rules with suboptimal rules for distributed detection of a constant signal corrupted by Gaussian noise. The numerical results obtained by conducted examples confirm the optimality of the derived decision rules.
{"title":"Impact of common observations in parallel distributed detection","authors":"Hao Chen, Tsang-Yi Wang","doi":"10.1109/DSP-SPE.2015.7369534","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369534","url":null,"abstract":"Distributed detection with dependent observations is always a challenging problem. The problem of detection with shared information has many applications when sensors have overlapped measurements, e.g., when distributed detection is performed in a security system where sensors have overlapped coverages. For this shared information scenario, we investigate the distributed detection problem in parallel fusion networks. The design problem is how to best utilize the common information at both the local sensors and the fusion center to achieve best possible performance. We derive the necessary condition for the optimal sensor decision rules for all sensors. In addition, we investigate the system performance by comparing the optimal rules with suboptimal rules for distributed detection of a constant signal corrupted by Gaussian noise. The numerical results obtained by conducted examples confirm the optimality of the derived decision rules.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"8 1","pages":"95-100"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81399870","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369577
Tianliang Peng, Yang Chen
Under-determined mixtures in blind source separation (BSS) are characterized by the case that they have more inputs than outputs. The classical independent component analysis (ICA) methods cannot be applied to the under-determined case. However, sparseness-based approaches can be applied to the under-determined BSS. Two steps method has been widely employed to solve the under-determined BSS problem: mixing matrix estimation and source recovery. Source recovery in under-determined BSS (UBSS) is an NP -hard problem and, therefore, does not have a closed form solution. In this paper, we proposed a new blind non-negative source recovery approach to the under-determined mixtures. The results presented in this paper are limited to non-negative sources. Simulation results illustrate the effectiveness of our method.
{"title":"Blind non-negative source recovery in under-determined mixtures","authors":"Tianliang Peng, Yang Chen","doi":"10.1109/DSP-SPE.2015.7369577","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369577","url":null,"abstract":"Under-determined mixtures in blind source separation (BSS) are characterized by the case that they have more inputs than outputs. The classical independent component analysis (ICA) methods cannot be applied to the under-determined case. However, sparseness-based approaches can be applied to the under-determined BSS. Two steps method has been widely employed to solve the under-determined BSS problem: mixing matrix estimation and source recovery. Source recovery in under-determined BSS (UBSS) is an NP -hard problem and, therefore, does not have a closed form solution. In this paper, we proposed a new blind non-negative source recovery approach to the under-determined mixtures. The results presented in this paper are limited to non-negative sources. Simulation results illustrate the effectiveness of our method.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"490 1","pages":"341-346"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75137664","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369535
D. S. Maughan, Ishmaal Erekson, Rajnikant Sharma
We propose the use of an Extended Kalman Filter (EKF) for reliable state estimation in order to permit advanced control of the tip of a flying inverted pendulum while maintaining safety. We demonstrate the capabilities of an EKF in tandem with an accurate model to overcome bad or false data from a multiple camera motion capture system used for positioning.
{"title":"Using Extended Kalman Filter for robust control of a flying inverted pendulum","authors":"D. S. Maughan, Ishmaal Erekson, Rajnikant Sharma","doi":"10.1109/DSP-SPE.2015.7369535","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369535","url":null,"abstract":"We propose the use of an Extended Kalman Filter (EKF) for reliable state estimation in order to permit advanced control of the tip of a flying inverted pendulum while maintaining safety. We demonstrate the capabilities of an EKF in tandem with an accurate model to overcome bad or false data from a multiple camera motion capture system used for positioning.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"18 1","pages":"101-106"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80798194","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369532
Juliana N. Saba, Son Ta, Tuan Nguyen, Cory Chilson, Jaewook Lee, Hussnain Ali, J. Hansen
In the United States, approximately 15% of adults (37.5M) age 18 and over report some trouble hearing[1,2], 1 in 8 people (13%, or 30M) 12 years or older have hearing loss in both ears[2,3], and approximately 3 out of 1000 children are born with hearing loss[2,4]. Educating the public, especially K-12 students, on the dangers of hearing loss is important. The ability to develop both a physical model of the middle ear along with signal processing simulation of effective impulsive sound suppression for hearing aids/cochlear implants will help provide a useful, hands-on experience for student education. Today, a functioning model of the bones of the middle ear exhibiting movement, forces, and sound conduction that highlight the importance of the ear's natural safety mechanism does not exist. This paper discusses the design of a standalone, interactive, and educational electro-mechanical model that exhibits the motion of the middle ear bones which include: (i) anatomical 3-bone configuration, (ii) fluid environment in the cochlea, and (iii) electrode stimulation to the auditory nerve cortex. This model has been assessed and approved by STEM/SEEC-UTDallas. To highlight the impact of noise protection on hearing, a complementary offline signal processing implementation is included to reduce the negative effects of impulsive-like sounds for cochlear implant users. An adaptable, mathematical relationship defines impulsive like sound conditions and reduces sound energy stimulated by the electrodes without reducing quality/intelligibility in the frequency ranges associated with speech. This algorithm was validated using a paired preference test, a quality test, and an intelligibility test to which the algorithm increased quality of sound by +18%.
{"title":"Developing an educational electro-mechanical model of the middle ear and impulse noise reduction algorithm for cochlear implant users","authors":"Juliana N. Saba, Son Ta, Tuan Nguyen, Cory Chilson, Jaewook Lee, Hussnain Ali, J. Hansen","doi":"10.1109/DSP-SPE.2015.7369532","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369532","url":null,"abstract":"In the United States, approximately 15% of adults (37.5M) age 18 and over report some trouble hearing[1,2], 1 in 8 people (13%, or 30M) 12 years or older have hearing loss in both ears[2,3], and approximately 3 out of 1000 children are born with hearing loss[2,4]. Educating the public, especially K-12 students, on the dangers of hearing loss is important. The ability to develop both a physical model of the middle ear along with signal processing simulation of effective impulsive sound suppression for hearing aids/cochlear implants will help provide a useful, hands-on experience for student education. Today, a functioning model of the bones of the middle ear exhibiting movement, forces, and sound conduction that highlight the importance of the ear's natural safety mechanism does not exist. This paper discusses the design of a standalone, interactive, and educational electro-mechanical model that exhibits the motion of the middle ear bones which include: (i) anatomical 3-bone configuration, (ii) fluid environment in the cochlea, and (iii) electrode stimulation to the auditory nerve cortex. This model has been assessed and approved by STEM/SEEC-UTDallas. To highlight the impact of noise protection on hearing, a complementary offline signal processing implementation is included to reduce the negative effects of impulsive-like sounds for cochlear implant users. An adaptable, mathematical relationship defines impulsive like sound conditions and reduces sound energy stimulated by the electrodes without reducing quality/intelligibility in the frequency ranges associated with speech. This algorithm was validated using a paired preference test, a quality test, and an intelligibility test to which the algorithm increased quality of sound by +18%.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"159 1","pages":"83-88"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90219184","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369526
A. Sangwan, J. Hansen, Dwight W. Irvin, S. Crutchfield, C. Greenwood
Understanding the language environments of early learners is critical in facilitating school success. Increasingly large scale projects (e.g., Providence Talks, Bridging the Word Gap) are investigating the language environments of young children in an attempt to better understand and facilitate language acquisition and development. The primary tool used to collect and analyze data related to the language environments of young learners is the LENA digital language processor (DLP). LENA allows for the continuous capture of language, primarily focused on a single child to adult interactions for up to 16 hrs. Subsequent analysis of the audio using spoken language technology (SLT) provides meaningful metrics such as total adult word count and conversational turns. One shortcoming of collecting continuous audio alone is that the physical context of adult-to-child or child-to-child communication is lost. In this study, we describe our recent data collection effort which combines the LENA and Ubisense sensors to allow for simultaneous capture of both spacial information along with speech and time. We are particularly interested in researching the relationship between the physical and language environments of children. In this study, we describe our collection methodology, results from initial probe experiments and our latest efforts in developing relevant SLT metrics. The new data and techniques described in this study can help in developing a richer understanding of how physical environments promote or encourage communication in early childhood classrooms. In theory, such speech and location technology can contribute to the design of future learning spaces specifically designed for typically developing children, or those with or at-risk for disabilities.
{"title":"Studying the relationship between physical and language environments of children: Who's speaking to whom and where?","authors":"A. Sangwan, J. Hansen, Dwight W. Irvin, S. Crutchfield, C. Greenwood","doi":"10.1109/DSP-SPE.2015.7369526","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369526","url":null,"abstract":"Understanding the language environments of early learners is critical in facilitating school success. Increasingly large scale projects (e.g., Providence Talks, Bridging the Word Gap) are investigating the language environments of young children in an attempt to better understand and facilitate language acquisition and development. The primary tool used to collect and analyze data related to the language environments of young learners is the LENA digital language processor (DLP). LENA allows for the continuous capture of language, primarily focused on a single child to adult interactions for up to 16 hrs. Subsequent analysis of the audio using spoken language technology (SLT) provides meaningful metrics such as total adult word count and conversational turns. One shortcoming of collecting continuous audio alone is that the physical context of adult-to-child or child-to-child communication is lost. In this study, we describe our recent data collection effort which combines the LENA and Ubisense sensors to allow for simultaneous capture of both spacial information along with speech and time. We are particularly interested in researching the relationship between the physical and language environments of children. In this study, we describe our collection methodology, results from initial probe experiments and our latest efforts in developing relevant SLT metrics. The new data and techniques described in this study can help in developing a richer understanding of how physical environments promote or encourage communication in early childhood classrooms. In theory, such speech and location technology can contribute to the design of future learning spaces specifically designed for typically developing children, or those with or at-risk for disabilities.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"7 1","pages":"49-54"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89181938","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 : 2015-08-01DOI: 10.1109/DSP-SPE.2015.7369575
D. Schneider-Luftman
In the analysis of Electroencephalograms (EEG), notably in their graphical modeling, the estimation of the spectral matrix and associated variables is of central importance. Often, when adjusting for the bandwidth of the spectral matrix estimate, singularity issues arise and information derived from the inverse spectral matrix is intractable. This requires the use of regularization methods, which have proven very popular in recent research. However, regularisation can be suboptimal for understanding connections within multichannel data and building graphical models. We propose a protocol that addresses this issue and that is specifically designed for spectral matrices of EEG data. It aims at maximising information retention for edge estimation in a graph, and unlike any existing regularisation method it solely relies on available data even at a conceptual level.
{"title":"Shrinkage estimation of spectral matrices: A EEG analysis centered approach","authors":"D. Schneider-Luftman","doi":"10.1109/DSP-SPE.2015.7369575","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369575","url":null,"abstract":"In the analysis of Electroencephalograms (EEG), notably in their graphical modeling, the estimation of the spectral matrix and associated variables is of central importance. Often, when adjusting for the bandwidth of the spectral matrix estimate, singularity issues arise and information derived from the inverse spectral matrix is intractable. This requires the use of regularization methods, which have proven very popular in recent research. However, regularisation can be suboptimal for understanding connections within multichannel data and building graphical models. We propose a protocol that addresses this issue and that is specifically designed for spectral matrices of EEG data. It aims at maximising information retention for edge estimation in a graph, and unlike any existing regularisation method it solely relies on available data even at a conceptual level.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"4 1","pages":"331-336"},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75301149","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 : 2015-07-08DOI: 10.1109/DSP-SPE.2015.7369524
Shervin Minaee, AmirAli Abdolrashidi, Yao Wang
Iris recognition has drawn a lot of attention since the mid-twentieth century. Among all biometric features, iris is known to possess a rich set of features. Different features have been used to perform iris recognition in the past. In this paper, two powerful sets of features are introduced to be used for iris recognition: scattering transform-based features and textural features. PCA is also applied on the extracted features to reduce the dimensionality of the feature vector while preserving most of the information of its initial value. Minimum distance classifier is used to perform template matching for each new test sample. The proposed scheme is tested on a well-known iris database, and showed promising results with the best accuracy rate of 99.2%.
{"title":"Iris recognition using scattering transform and textural features","authors":"Shervin Minaee, AmirAli Abdolrashidi, Yao Wang","doi":"10.1109/DSP-SPE.2015.7369524","DOIUrl":"https://doi.org/10.1109/DSP-SPE.2015.7369524","url":null,"abstract":"Iris recognition has drawn a lot of attention since the mid-twentieth century. Among all biometric features, iris is known to possess a rich set of features. Different features have been used to perform iris recognition in the past. In this paper, two powerful sets of features are introduced to be used for iris recognition: scattering transform-based features and textural features. PCA is also applied on the extracted features to reduce the dimensionality of the feature vector while preserving most of the information of its initial value. Minimum distance classifier is used to perform template matching for each new test sample. The proposed scheme is tested on a well-known iris database, and showed promising results with the best accuracy rate of 99.2%.","PeriodicalId":91992,"journal":{"name":"2015 IEEE Signal Processing and Signal Processing Education Workshop (SP/SPE)","volume":"170 1","pages":"37-42"},"PeriodicalIF":0.0,"publicationDate":"2015-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79203644","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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