The Experts below are selected from a list of 9021 Experts worldwide ranked by ideXlab platform
Hiroshi Nakajima - One of the best experts on this subject based on the ideXlab platform.
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an effective approach for Iris recognition using phase based Image matching
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Koichi Ito, Hiroshi NakajimaAbstract:This paper presents an efficient algorithm for Iris recognition using phase-based Image matching - an Image matching technique using phase components in 2D discrete Fourier transforms (DFTs) of given Images. Experimental evaluation using the CASIA Iris Image databases (versions 1.0 and 2.0) and Iris challenge evaluation (ICE) 2005 database clearly demonstrates that the use of phase components of Iris Images makes it possible to achieve highly accurate Iris recognition with a simple matching algorithm. This paper also discusses the major implementation issues of our algorithm. In order to reduce the size of Iris data and to prevent the visibility of Iris Images, we introduce the idea of 2D Fourier phase code (FPC) for representing Iris information. The 2D FPC is particularly useful for implementing compact Iris recognition devices using state-of-the-art digital signal processing (DSP) technology.
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an effective approach for Iris recognition using phase based Image matching
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Koichi Ito, Hiroshi NakajimaAbstract:This paper presents an efficient algorithm for Iris recognition using phase-based Image matching - an Image matching technique using phase components in 2D discrete Fourier transforms (DFTs) of given Images. Experimental evaluation using the CASIA Iris Image databases (versions 1.0 and 2.0) and Iris challenge evaluation (ICE) 2005 database clearly demonstrates that the use of phase components of Iris Images makes it possible to achieve highly accurate Iris recognition with a simple matching algorithm. This paper also discusses the major implementation issues of our algorithm. In order to reduce the size of Iris data and to prevent the visibility of Iris Images, we introduce the idea of 2D Fourier phase code (FPC) for representing Iris information. The 2D FPC is particularly useful for implementing compact Iris recognition devices using state-of-the-art digital signal processing (DSP) technology.
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a phase based Iris recognition algorithm
Lecture Notes in Computer Science, 2006Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Hiroshi NakajimaAbstract:This paper presents an efficient algorithm for Iris recognition using phase-based Image matching. The use of phase components in two-dimensional discrete Fourier transforms of Iris Images makes possible to achieve highly robust Iris recognition with a simple matching algorithm. Experimental evaluation using the CASIA Iris Image database (ver. 1.0 and ver. 2.0) clearly demonstrates an efficient performance of the proposed algorithm.
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an efficient Iris recognition algorithm using phase based Image matching
International Conference on Image Processing, 2005Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Hiroshi NakajimaAbstract:A major approach for Iris recognition today is to generate feature vectors corresponding to individual Iris Images and to perform Iris matching based on some distance metrics. One of the difficult problems in feature-based Iris recognition is that the matching performance is significantly influenced by many parameters in feature extraction process, which may vary depending on environmental factors of Image acquisition. This paper presents an efficient algorithm for Iris recognition using phase-based Image matching. The use of phase components in 2D (two-dimensional) discrete Fourier transforms of Iris Images makes possible to achieve highly robust Iris recognition in a unified fashion with a simple matching algorithm. Experimental evaluation using an Iris Image database clearly demonstrates an efficient matching performance of the proposed algorithm.
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an efficient Iris recognition algorithm using phase based Image matching
International Conference on Image Processing, 2005Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Koichi Ito, Hiroshi NakajimaAbstract:A major approach for Iris recognition today is to generate feature vectors corresponding to individual Iris Images and to perform Iris matching based on some distance metrics. One of the difficult problems in feature-based Iris recognition is that the matching performance is significantly influenced by many parameters in feature extraction process, which may vary depending on environmental factors of Image acquisition. This paper presents an efficient algorithm for Iris recognition using phase-based Image matching. The use of phase components in 2D (two-dimensional) discrete Fourier transforms of Iris Images makes possible to achieve highly robust Iris recognition in a unified fashion with a simple matching algorithm. Experimental evaluation using an Iris Image database clearly demonstrates an efficient matching performance of the proposed algorithm.
Kang Ryoung Park - One of the best experts on this subject based on the ideXlab platform.
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fake Iris detection based on 3d structure of Iris pattern
International Journal of Imaging Systems and Technology, 2010Co-Authors: Eui Chul Lee, Kang Ryoung ParkAbstract:A new fake Iris detection method based on 3D feature of Iris pattern is proposed. In pervious researches, they did not consider 3D structure of Iris pattern, but only used 2D features of Iris Image. However, in our method, by using four near infra-red (NIR) illuminators attached on the left and right sides of Iris camera, we could obtain the Iris Image in which the 3D structure of Iris pattern could be shown distinctively. Based on that, we could determine the live or fake Iris by wavelet analysis of the 3D feature of Iris pattern. Experimental result showed that the Equal Error Rate (EER) of determining the live or fake Iris was 0.33p. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 162–166, 2010
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real time Image restoration for Iris recognition systems
Systems Man and Cybernetics, 2007Co-Authors: Byung Jun Kang, Kang Ryoung ParkAbstract:In the field of biometrics, it has been reported that Iris recognition techniques have shown high levels of accuracy because unique patterns of the human Iris, which has very many degrees of freedom, are used. However, because conventional Iris cameras have small depth-of-field (DOF) areas, input Iris Images can easily be blurred, which can lead to lower recognition performance, since Iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time Iris Image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: (1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input Iris Images; (2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; (3) because the PSF parameter can be obtained by using a predetermined equation, Iris Image restoration can be done in real-time; (4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and (5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of Image blurring. Experimental results showed that Iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous Iris-restoration methods.
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real time Image restoration for Iris recognition systems
Systems Man and Cybernetics, 2007Co-Authors: Byung Jun Kang, Kang Ryoung ParkAbstract:In the field of biometrics, it has been reported that Iris recognition techniques have shown high levels of accuracy because unique patterns of the human Iris, which has very many degrees of freedom, are used. However, because conventional Iris cameras have small depth-of-field (DOF) areas, input Iris Images can easily be blurred, which can lead to lower recognition performance, since Iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time Iris Image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: (1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input Iris Images; (2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; (3) because the PSF parameter can be obtained by using a predetermined equation, Iris Image restoration can be done in real-time; (4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and (5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of Image blurring. Experimental results showed that Iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous Iris-restoration methods.
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fake Iris detection by using purkinje Image
Lecture Notes in Computer Science, 2006Co-Authors: Eui Chul Lee, Kang Ryoung Park, Jaihie KimAbstract:Fake Iris detection is to detect and defeat a fake (forgery) Iris Image input. To solve the problems of previous researches on fake Iris detection, we propose the new method of detecting fake Iris attack based on the Purkinje Image. Especially, we calculated the theoretical positions and distances between the Purkinje Images based on the human eye model and the performance of fake detection algorithm could be much enhanced by such information. Experimental results showed that the FAR (False Acceptance Rate for accepting fake Iris as live one) was 0.33% and FRR(False Rejection Rate of rejecting live Iris as fake one) was 0.33%.
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a study on Iris Image restoration
Lecture Notes in Computer Science, 2005Co-Authors: Byung Jun Kang, Kang Ryoung ParkAbstract:Because Iris recognition uses the unique patterns of the human Iris, it is essential to acquire the Iris Images at high quality for accurate recognition. Defocusing reduces the quality of the Iris Image and the performance of Iris recognition, consequently. In order to acquire a focused Iris Image at high quality, an Iris recognition camera must control the focal length of the moving lens. However, that causes the cost and size of Iris camera to be increased and that needs complicated auto-focusing algorithm, also. To overcome such problems, we propose new method of Iris Image restoration. Experimental results show that the total recognition time is reduced as much as 390ms on average with the proposed restoration algorithm.
Kazuyuki Miyazawa - One of the best experts on this subject based on the ideXlab platform.
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an effective approach for Iris recognition using phase based Image matching
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Koichi Ito, Hiroshi NakajimaAbstract:This paper presents an efficient algorithm for Iris recognition using phase-based Image matching - an Image matching technique using phase components in 2D discrete Fourier transforms (DFTs) of given Images. Experimental evaluation using the CASIA Iris Image databases (versions 1.0 and 2.0) and Iris challenge evaluation (ICE) 2005 database clearly demonstrates that the use of phase components of Iris Images makes it possible to achieve highly accurate Iris recognition with a simple matching algorithm. This paper also discusses the major implementation issues of our algorithm. In order to reduce the size of Iris data and to prevent the visibility of Iris Images, we introduce the idea of 2D Fourier phase code (FPC) for representing Iris information. The 2D FPC is particularly useful for implementing compact Iris recognition devices using state-of-the-art digital signal processing (DSP) technology.
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an effective approach for Iris recognition using phase based Image matching
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Koichi Ito, Hiroshi NakajimaAbstract:This paper presents an efficient algorithm for Iris recognition using phase-based Image matching - an Image matching technique using phase components in 2D discrete Fourier transforms (DFTs) of given Images. Experimental evaluation using the CASIA Iris Image databases (versions 1.0 and 2.0) and Iris challenge evaluation (ICE) 2005 database clearly demonstrates that the use of phase components of Iris Images makes it possible to achieve highly accurate Iris recognition with a simple matching algorithm. This paper also discusses the major implementation issues of our algorithm. In order to reduce the size of Iris data and to prevent the visibility of Iris Images, we introduce the idea of 2D Fourier phase code (FPC) for representing Iris information. The 2D FPC is particularly useful for implementing compact Iris recognition devices using state-of-the-art digital signal processing (DSP) technology.
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a phase based Iris recognition algorithm
Lecture Notes in Computer Science, 2006Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Hiroshi NakajimaAbstract:This paper presents an efficient algorithm for Iris recognition using phase-based Image matching. The use of phase components in two-dimensional discrete Fourier transforms of Iris Images makes possible to achieve highly robust Iris recognition with a simple matching algorithm. Experimental evaluation using the CASIA Iris Image database (ver. 1.0 and ver. 2.0) clearly demonstrates an efficient performance of the proposed algorithm.
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an efficient Iris recognition algorithm using phase based Image matching
International Conference on Image Processing, 2005Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Hiroshi NakajimaAbstract:A major approach for Iris recognition today is to generate feature vectors corresponding to individual Iris Images and to perform Iris matching based on some distance metrics. One of the difficult problems in feature-based Iris recognition is that the matching performance is significantly influenced by many parameters in feature extraction process, which may vary depending on environmental factors of Image acquisition. This paper presents an efficient algorithm for Iris recognition using phase-based Image matching. The use of phase components in 2D (two-dimensional) discrete Fourier transforms of Iris Images makes possible to achieve highly robust Iris recognition in a unified fashion with a simple matching algorithm. Experimental evaluation using an Iris Image database clearly demonstrates an efficient matching performance of the proposed algorithm.
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an efficient Iris recognition algorithm using phase based Image matching
International Conference on Image Processing, 2005Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Koichi Ito, Hiroshi NakajimaAbstract:A major approach for Iris recognition today is to generate feature vectors corresponding to individual Iris Images and to perform Iris matching based on some distance metrics. One of the difficult problems in feature-based Iris recognition is that the matching performance is significantly influenced by many parameters in feature extraction process, which may vary depending on environmental factors of Image acquisition. This paper presents an efficient algorithm for Iris recognition using phase-based Image matching. The use of phase components in 2D (two-dimensional) discrete Fourier transforms of Iris Images makes possible to achieve highly robust Iris recognition in a unified fashion with a simple matching algorithm. Experimental evaluation using an Iris Image database clearly demonstrates an efficient matching performance of the proposed algorithm.
Byung Jun Kang - One of the best experts on this subject based on the ideXlab platform.
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real time Image restoration for Iris recognition systems
Systems Man and Cybernetics, 2007Co-Authors: Byung Jun Kang, Kang Ryoung ParkAbstract:In the field of biometrics, it has been reported that Iris recognition techniques have shown high levels of accuracy because unique patterns of the human Iris, which has very many degrees of freedom, are used. However, because conventional Iris cameras have small depth-of-field (DOF) areas, input Iris Images can easily be blurred, which can lead to lower recognition performance, since Iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time Iris Image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: (1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input Iris Images; (2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; (3) because the PSF parameter can be obtained by using a predetermined equation, Iris Image restoration can be done in real-time; (4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and (5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of Image blurring. Experimental results showed that Iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous Iris-restoration methods.
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real time Image restoration for Iris recognition systems
Systems Man and Cybernetics, 2007Co-Authors: Byung Jun Kang, Kang Ryoung ParkAbstract:In the field of biometrics, it has been reported that Iris recognition techniques have shown high levels of accuracy because unique patterns of the human Iris, which has very many degrees of freedom, are used. However, because conventional Iris cameras have small depth-of-field (DOF) areas, input Iris Images can easily be blurred, which can lead to lower recognition performance, since Iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time Iris Image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: (1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input Iris Images; (2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; (3) because the PSF parameter can be obtained by using a predetermined equation, Iris Image restoration can be done in real-time; (4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and (5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of Image blurring. Experimental results showed that Iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous Iris-restoration methods.
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a study on Iris Image restoration
Lecture Notes in Computer Science, 2005Co-Authors: Byung Jun Kang, Kang Ryoung ParkAbstract:Because Iris recognition uses the unique patterns of the human Iris, it is essential to acquire the Iris Images at high quality for accurate recognition. Defocusing reduces the quality of the Iris Image and the performance of Iris recognition, consequently. In order to acquire a focused Iris Image at high quality, an Iris recognition camera must control the focal length of the moving lens. However, that causes the cost and size of Iris camera to be increased and that needs complicated auto-focusing algorithm, also. To overcome such problems, we propose new method of Iris Image restoration. Experimental results show that the total recognition time is reduced as much as 390ms on average with the proposed restoration algorithm.
Koji Kobayashi - One of the best experts on this subject based on the ideXlab platform.
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an effective approach for Iris recognition using phase based Image matching
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Koichi Ito, Hiroshi NakajimaAbstract:This paper presents an efficient algorithm for Iris recognition using phase-based Image matching - an Image matching technique using phase components in 2D discrete Fourier transforms (DFTs) of given Images. Experimental evaluation using the CASIA Iris Image databases (versions 1.0 and 2.0) and Iris challenge evaluation (ICE) 2005 database clearly demonstrates that the use of phase components of Iris Images makes it possible to achieve highly accurate Iris recognition with a simple matching algorithm. This paper also discusses the major implementation issues of our algorithm. In order to reduce the size of Iris data and to prevent the visibility of Iris Images, we introduce the idea of 2D Fourier phase code (FPC) for representing Iris information. The 2D FPC is particularly useful for implementing compact Iris recognition devices using state-of-the-art digital signal processing (DSP) technology.
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an effective approach for Iris recognition using phase based Image matching
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Koichi Ito, Hiroshi NakajimaAbstract:This paper presents an efficient algorithm for Iris recognition using phase-based Image matching - an Image matching technique using phase components in 2D discrete Fourier transforms (DFTs) of given Images. Experimental evaluation using the CASIA Iris Image databases (versions 1.0 and 2.0) and Iris challenge evaluation (ICE) 2005 database clearly demonstrates that the use of phase components of Iris Images makes it possible to achieve highly accurate Iris recognition with a simple matching algorithm. This paper also discusses the major implementation issues of our algorithm. In order to reduce the size of Iris data and to prevent the visibility of Iris Images, we introduce the idea of 2D Fourier phase code (FPC) for representing Iris information. The 2D FPC is particularly useful for implementing compact Iris recognition devices using state-of-the-art digital signal processing (DSP) technology.
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a phase based Iris recognition algorithm
Lecture Notes in Computer Science, 2006Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Hiroshi NakajimaAbstract:This paper presents an efficient algorithm for Iris recognition using phase-based Image matching. The use of phase components in two-dimensional discrete Fourier transforms of Iris Images makes possible to achieve highly robust Iris recognition with a simple matching algorithm. Experimental evaluation using the CASIA Iris Image database (ver. 1.0 and ver. 2.0) clearly demonstrates an efficient performance of the proposed algorithm.
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an efficient Iris recognition algorithm using phase based Image matching
International Conference on Image Processing, 2005Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Hiroshi NakajimaAbstract:A major approach for Iris recognition today is to generate feature vectors corresponding to individual Iris Images and to perform Iris matching based on some distance metrics. One of the difficult problems in feature-based Iris recognition is that the matching performance is significantly influenced by many parameters in feature extraction process, which may vary depending on environmental factors of Image acquisition. This paper presents an efficient algorithm for Iris recognition using phase-based Image matching. The use of phase components in 2D (two-dimensional) discrete Fourier transforms of Iris Images makes possible to achieve highly robust Iris recognition in a unified fashion with a simple matching algorithm. Experimental evaluation using an Iris Image database clearly demonstrates an efficient matching performance of the proposed algorithm.
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an efficient Iris recognition algorithm using phase based Image matching
International Conference on Image Processing, 2005Co-Authors: Kazuyuki Miyazawa, Takafumi Aoki, Koji Kobayashi, Koichi Ito, Hiroshi NakajimaAbstract:A major approach for Iris recognition today is to generate feature vectors corresponding to individual Iris Images and to perform Iris matching based on some distance metrics. One of the difficult problems in feature-based Iris recognition is that the matching performance is significantly influenced by many parameters in feature extraction process, which may vary depending on environmental factors of Image acquisition. This paper presents an efficient algorithm for Iris recognition using phase-based Image matching. The use of phase components in 2D (two-dimensional) discrete Fourier transforms of Iris Images makes possible to achieve highly robust Iris recognition in a unified fashion with a simple matching algorithm. Experimental evaluation using an Iris Image database clearly demonstrates an efficient matching performance of the proposed algorithm.