Pub Date : 2009-09-28DOI: 10.1109/BTAS.2009.5339070
Mohammad Nayeem Teli, J. Beveridge
This research presents a study of the geometry of the face manifold as a person changes their horizontal pose from one profile to another. Although, a lot of research has gone into aspects of determining an ideal pose for pose invariant face recognition, less has been done to present the manifold of the faces presented by these pose variations. The novelty of our approach lies in the presentation of a finely sampled profile-to-profile dataset that is analyzed using Locally Linear Embedding (LLE) to estimate the curvature of these manifolds. Our results indicate that the profile-to-profile manifold is less curved, hence more linear, in the region around the frontal view than for any other region of the manifold, i.e. pose.
{"title":"Pose manifold curvature is typically less near frontal face views","authors":"Mohammad Nayeem Teli, J. Beveridge","doi":"10.1109/BTAS.2009.5339070","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339070","url":null,"abstract":"This research presents a study of the geometry of the face manifold as a person changes their horizontal pose from one profile to another. Although, a lot of research has gone into aspects of determining an ideal pose for pose invariant face recognition, less has been done to present the manifold of the faces presented by these pose variations. The novelty of our approach lies in the presentation of a finely sampled profile-to-profile dataset that is analyzed using Locally Linear Embedding (LLE) to estimate the curvature of these manifolds. Our results indicate that the profile-to-profile manifold is less curved, hence more linear, in the region around the frontal view than for any other region of the manifold, i.e. pose.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126870588","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 : 2009-09-28DOI: 10.1109/BTAS.2009.5339012
Zhiming Liu, Chengjun Liu, Qingchuan Tao
This paper presents a novel method for face recognition. First, we generate the new image representation from the decorrelated hybrid color configurations rather than RGB color space via a learning algorithm. The learning algorithm, Principal Component Analysis (PCA) plus Fisher Linear Discriminant analysis (FLD), is able to derive the desired color transformation to generate a discriminating image representation that is optimal for face recognition. Second, we partition face image into some small patches, each of which can obtain its own color transformation, to reduce the effect of illumination variations. Thus, a patch-based novel image representation method is proposed for face recognition. Experiments on the Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 show that the proposed method outperforms gray-scale image and some recent methods in face recognition.
提出了一种新的人脸识别方法。首先，我们通过学习算法从去相关的混合颜色配置而不是RGB颜色空间生成新的图像表示。学习算法，主成分分析(PCA)加上Fisher线性判别分析(FLD)，能够得出所需的颜色变换，以生成最适合人脸识别的判别图像表示。其次，我们将人脸图像分割成一些小块，每个小块都可以获得自己的颜色变换，以减少光照变化的影响。为此，提出了一种基于补丁的人脸识别图像表示方法。在Face Recognition Grand Challenge (FRGC) version 2上的实验表明，该方法在人脸识别方面的性能优于灰度图像和一些最新的人脸识别方法。
{"title":"Learning-based image representation and method for face recognition","authors":"Zhiming Liu, Chengjun Liu, Qingchuan Tao","doi":"10.1109/BTAS.2009.5339012","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339012","url":null,"abstract":"This paper presents a novel method for face recognition. First, we generate the new image representation from the decorrelated hybrid color configurations rather than RGB color space via a learning algorithm. The learning algorithm, Principal Component Analysis (PCA) plus Fisher Linear Discriminant analysis (FLD), is able to derive the desired color transformation to generate a discriminating image representation that is optimal for face recognition. Second, we partition face image into some small patches, each of which can obtain its own color transformation, to reduce the effect of illumination variations. Thus, a patch-based novel image representation method is proposed for face recognition. Experiments on the Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 show that the proposed method outperforms gray-scale image and some recent methods in face recognition.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115538542","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 : 2009-09-28DOI: 10.1109/BTAS.2009.5339043
Hanan A. Al Nizami, Jeremy P. Adkins-Hill, Yong Zhang, J. Sullins, Christine McCullough, Shaun J. Canavan, L. Yin
The past decade has witnessed a significant progress in biometric technologies, to a large degree, due to the availability of a wide variety of public databases that enable benchmark performance evaluations. In this paper, we describe a new database that includes: (i) Rotating head videos of 259 subjects; (ii) 250 hand-drawn face sketches of 50 subjects. Rotating head videos were acquired under both normal indoor lighting and shadow conditions. Each video captured four expressions: neutral, smile, surprise, and anger. For each subject, video frames of ten pose angles were manually labeled using reference images and empirical rules, to facilitate the investigation of multi-frame fusion. The database can also be used to study 3D face recognition by reconstructing a 3D face model from videos. In addition, this is the only currently available database that has a large number of face sketches drawn by multiple artists. The face sketches are valuable resource for many researches, such as forensic analysis of eyewitness recollection, impact assessment of face degradation on recognition rate, as well as comparative evaluation of sketch recognitions by humans and algorithms.
{"title":"A biometric database with rotating head videos and hand-drawn face sketches","authors":"Hanan A. Al Nizami, Jeremy P. Adkins-Hill, Yong Zhang, J. Sullins, Christine McCullough, Shaun J. Canavan, L. Yin","doi":"10.1109/BTAS.2009.5339043","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339043","url":null,"abstract":"The past decade has witnessed a significant progress in biometric technologies, to a large degree, due to the availability of a wide variety of public databases that enable benchmark performance evaluations. In this paper, we describe a new database that includes: (i) Rotating head videos of 259 subjects; (ii) 250 hand-drawn face sketches of 50 subjects. Rotating head videos were acquired under both normal indoor lighting and shadow conditions. Each video captured four expressions: neutral, smile, surprise, and anger. For each subject, video frames of ten pose angles were manually labeled using reference images and empirical rules, to facilitate the investigation of multi-frame fusion. The database can also be used to study 3D face recognition by reconstructing a 3D face model from videos. In addition, this is the only currently available database that has a large number of face sketches drawn by multiple artists. The face sketches are valuable resource for many researches, such as forensic analysis of eyewitness recollection, impact assessment of face degradation on recognition rate, as well as comparative evaluation of sketch recognitions by humans and algorithms.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116602479","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 : 2009-09-28DOI: 10.1109/BTAS.2009.5339057
Keshav Seshadri, M. Savvides
In this paper we present an improved method for locating facial landmarks in images containing frontal faces using a modified Active Shape Model. Our main contributions include the use of an optimal number of facial landmark points, better profiling methods during the fitting stage and the development of a more suitable optimization metric to determine the best location of the landmarks compared to the simplistic minimum Mahalanobis distance criteria used to date. We build a subspace to model variations of appearance around each facial landmark and use this subspace to enhance the accuracy of the fitting process around each landmark. This enhancement provides a significant improvement in fitting and simultaneously determines which points were poorly fitted using reconstruction error, thus allowing for automatic correction or interpolation of any poorly fitted points. Our implementation, with the above mentioned improvements, leads to extremely accurate results even when dealing with faces with expressions, slight pose variations and in-plane rotations. Experiments conducted on test sets drawn from three databases (NIST Multiple Biometric Grand Challenge-2008 (MBGC-2008), CMU Multi-PIE and the Japanese Female Facial Expression (JAFFE) database) show that our proposed approach leads to far better performance compared to the classical Active Shape Model of Cootes et al. and other traditional methods and provides a robust automatic facial landmark annotation which is the first critical step in face registration, pose correction and face recognition.
{"title":"Robust modified Active Shape Model for automatic facial landmark annotation of frontal faces","authors":"Keshav Seshadri, M. Savvides","doi":"10.1109/BTAS.2009.5339057","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339057","url":null,"abstract":"In this paper we present an improved method for locating facial landmarks in images containing frontal faces using a modified Active Shape Model. Our main contributions include the use of an optimal number of facial landmark points, better profiling methods during the fitting stage and the development of a more suitable optimization metric to determine the best location of the landmarks compared to the simplistic minimum Mahalanobis distance criteria used to date. We build a subspace to model variations of appearance around each facial landmark and use this subspace to enhance the accuracy of the fitting process around each landmark. This enhancement provides a significant improvement in fitting and simultaneously determines which points were poorly fitted using reconstruction error, thus allowing for automatic correction or interpolation of any poorly fitted points. Our implementation, with the above mentioned improvements, leads to extremely accurate results even when dealing with faces with expressions, slight pose variations and in-plane rotations. Experiments conducted on test sets drawn from three databases (NIST Multiple Biometric Grand Challenge-2008 (MBGC-2008), CMU Multi-PIE and the Japanese Female Facial Expression (JAFFE) database) show that our proposed approach leads to far better performance compared to the classical Active Shape Model of Cootes et al. and other traditional methods and provides a robust automatic facial landmark annotation which is the first critical step in face registration, pose correction and face recognition.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117094099","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 : 2009-09-28DOI: 10.1109/BTAS.2009.5339079
Mayank Vatsa, Richa Singh, A. Noore, Keith B. Morris
Recent cases such as Commonwealth v Patterson show that there is a lack of research in how to process and recognize simultaneous fingerprint impressions, especially when none of the latent prints in the cluster could be individually matched. SWGFAST released the first version of the standard on simultaneous impression examination that can help fingerprint examiners to systematically compare latent simultaneous impressions to a known ten-print card. However, when the individual is not known, the simultaneous fingerprint impressions have to be compared using a large database of reference ten-prints, making the process very challenging. This paper introduces the research problem of identifying simultaneous latent fingerprint impressions to the community and presents a semi-automatic approach to process the impressions of any individual. The approach generates a list of top matches and latent fingerprint examiners can then examine them for individualization. Using a fingerprint database that contains simultaneous latent impressions, we analyze the performance of the proposed approach obtained by matching simultaneous impressions with the gallery database.
最近的英联邦诉帕特森案(Commonwealth v Patterson)表明，缺乏对如何处理和识别同时存在的指纹印象的研究，特别是当集群中没有一个潜在指纹可以单独匹配时。SWGFAST发布了第一个版本的同时印痕检查标准，可以帮助指纹审查员系统地将潜在的同时印痕与已知的十印卡进行比较。然而，当不知道个人身份时，必须使用一个大型的参考指纹数据库来比较同时产生的指纹印象，这使得这一过程非常具有挑战性。本文介绍了社会上对同时潜在指纹印识别的研究问题，提出了一种半自动处理任意个体指纹印的方法。该方法生成一个顶级匹配列表，然后潜在指纹检测器可以对它们进行个性化检查。使用包含同时潜在印象的指纹数据库，我们通过将同时印象与画廊数据库进行匹配来分析所提出的方法的性能。
{"title":"Simultaneous latent fingerprint recognition: A preliminary study","authors":"Mayank Vatsa, Richa Singh, A. Noore, Keith B. Morris","doi":"10.1109/BTAS.2009.5339079","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339079","url":null,"abstract":"Recent cases such as Commonwealth v Patterson show that there is a lack of research in how to process and recognize simultaneous fingerprint impressions, especially when none of the latent prints in the cluster could be individually matched. SWGFAST released the first version of the standard on simultaneous impression examination that can help fingerprint examiners to systematically compare latent simultaneous impressions to a known ten-print card. However, when the individual is not known, the simultaneous fingerprint impressions have to be compared using a large database of reference ten-prints, making the process very challenging. This paper introduces the research problem of identifying simultaneous latent fingerprint impressions to the community and presents a semi-automatic approach to process the impressions of any individual. The approach generates a list of top matches and latent fingerprint examiners can then examine them for individualization. Using a fingerprint database that contains simultaneous latent impressions, we analyze the performance of the proposed approach obtained by matching simultaneous impressions with the gallery database.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128294282","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 : 2009-09-28DOI: 10.1109/BTAS.2009.5339082
K. Ricanek, Yishi Wang, Cuixian Chen, S. J. Simmons
Age estimation from digital pictures of the face is a very promising research field that is now receiving wide attention. As with any good research problem, face age-estimation is wrought with many challenging interactions that cannot easily be separated out. In general, aging patterns are well understood for all humans, however, these patterns become confounded by intrinsic factors of genetics, gender differences, and ethnic deviations and, equally as important, extrinsic factors of the environment and behavior choices (i.e. sun exposure, drugs, cigarettes, etc). This novel work focuses on the development of a generalized multi-ethnic age-estimation technique — the first of its kind. In addition to the novelty of this approach, the system's overall performance measure (MAE) is “on par” with algorithms that are tuned for a specific ethnic group. Further, the proposed system performance proves to be far more stable across age than the best published results.
{"title":"Generalized multi-ethnic face age-estimation","authors":"K. Ricanek, Yishi Wang, Cuixian Chen, S. J. Simmons","doi":"10.1109/BTAS.2009.5339082","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339082","url":null,"abstract":"Age estimation from digital pictures of the face is a very promising research field that is now receiving wide attention. As with any good research problem, face age-estimation is wrought with many challenging interactions that cannot easily be separated out. In general, aging patterns are well understood for all humans, however, these patterns become confounded by intrinsic factors of genetics, gender differences, and ethnic deviations and, equally as important, extrinsic factors of the environment and behavior choices (i.e. sun exposure, drugs, cigarettes, etc). This novel work focuses on the development of a generalized multi-ethnic age-estimation technique — the first of its kind. In addition to the novelty of this approach, the system's overall performance measure (MAE) is “on par” with algorithms that are tuned for a specific ethnic group. Further, the proposed system performance proves to be far more stable across age than the best published results.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131980291","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 : 2009-09-28DOI: 10.1109/BTAS.2009.5339069
A. Uhl, Peter Wild
With the large scale deployment of biometrics for access control in private and public places, systems are faced the challenge of processing a diverse range of people. Most systems have been well evaluated for adults, however, their application in schools, or for private door access control, raises the question, whether there exists significant difference in performance between age groups in general and between kids and adults in particular. This paper targets an evaluation of the impact of children as biometric users on recognition accuracy for a series of hand-based modalities: Fingerprint, Palmprint, Hand-geometry and Digitprint. Furthermore, we try to analyze reasons for child-aging effects on performance at both feature and instance level using our database of 301 kids and 86 adults.
{"title":"Comparing verification performance of kids and adults for Fingerprint, Palmprint, Hand-geometry and Digitprint biometrics","authors":"A. Uhl, Peter Wild","doi":"10.1109/BTAS.2009.5339069","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339069","url":null,"abstract":"With the large scale deployment of biometrics for access control in private and public places, systems are faced the challenge of processing a diverse range of people. Most systems have been well evaluated for adults, however, their application in schools, or for private door access control, raises the question, whether there exists significant difference in performance between age groups in general and between kids and adults in particular. This paper targets an evaluation of the impact of children as biometric users on recognition accuracy for a series of hand-based modalities: Fingerprint, Palmprint, Hand-geometry and Digitprint. Furthermore, we try to analyze reasons for child-aging effects on performance at both feature and instance level using our database of 301 kids and 86 adults.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133830566","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 : 2009-09-28DOI: 10.1109/BTAS.2009.5339019
P. Perakis, G. Passalis, T. Theoharis, G. Toderici, I. Kakadiaris
Three-dimensional face recognition has lately received much attention due to its robustness in the presence of lighting and pose variations. However, certain pose variations often result in missing facial data. This is common in realistic scenarios, such as uncontrolled environments and uncooperative subjects. Most previous 3D face recognition methods do not handle extensive missing data as they rely on frontal scans. Currently, there is no method to perform recognition across scans of different poses. A unified method that addresses the partial matching problem is proposed. Both frontal and side (left or right) facial scans are handled in a way that allows interpose retrieval operations. The main contributions of this paper include a novel 3D landmark detector and a deformable model framework that supports symmetric fitting. The landmark detector is utilized to detect the pose of the facial scan. This information is used to mark areas of missing data and to roughly register the facial scan with an Annotated Face Model (AFM). The AFM is fitted using a deformable model framework that introduces the method of exploiting facial symmetry where data are missing. Subsequently, a geometry image is extracted from the fitted AFM that is independent of the original pose of the facial scan. Retrieval operations, such as face identification, are then performed on a wavelet domain representation of the geometry image. Thorough testing was performed by combining the largest publicly available databases. To the best of our knowledge, this is the first method that handles side scans with extensive missing data (e.g., up to half of the face missing).
{"title":"Partial matching of interpose 3D facial data for face recognition","authors":"P. Perakis, G. Passalis, T. Theoharis, G. Toderici, I. Kakadiaris","doi":"10.1109/BTAS.2009.5339019","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339019","url":null,"abstract":"Three-dimensional face recognition has lately received much attention due to its robustness in the presence of lighting and pose variations. However, certain pose variations often result in missing facial data. This is common in realistic scenarios, such as uncontrolled environments and uncooperative subjects. Most previous 3D face recognition methods do not handle extensive missing data as they rely on frontal scans. Currently, there is no method to perform recognition across scans of different poses. A unified method that addresses the partial matching problem is proposed. Both frontal and side (left or right) facial scans are handled in a way that allows interpose retrieval operations. The main contributions of this paper include a novel 3D landmark detector and a deformable model framework that supports symmetric fitting. The landmark detector is utilized to detect the pose of the facial scan. This information is used to mark areas of missing data and to roughly register the facial scan with an Annotated Face Model (AFM). The AFM is fitted using a deformable model framework that introduces the method of exploiting facial symmetry where data are missing. Subsequently, a geometry image is extracted from the fitted AFM that is independent of the original pose of the facial scan. Retrieval operations, such as face identification, are then performed on a wavelet domain representation of the geometry image. Thorough testing was performed by combining the largest publicly available databases. To the best of our knowledge, this is the first method that handles side scans with extensive missing data (e.g., up to half of the face missing).","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132146279","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 : 2009-09-28DOI: 10.1109/BTAS.2009.5339077
R. D. Labati, V. Piuri, F. Scotti
The paper presents two different methods to deal with the problem of iris segmentation: an agent-based method capable to localize the center of the pupil and a method to process the iris boundaries by a multiple views approach. In the first method, an agent corresponds to the coordinates of a specific point of analysis in the input image. A population of agents is deployed in the input image, then, each agent collects local information concerning the intensity patterns visible in its region of interest. By iterations, an agent changes its position accordingly to the local properties, moving towards the estimation of the pupil center. If no available information is present in its region of interest, the agent will move itself along a random walk. After few iterations, the population tends to spread and then concentrate in the inner portion of the pupil. Once the center of the pupil has been located, the inner and outer iris boundaries are refined by an approach based on multiple views analysis. This method starts with a set of points that can be considered as an approximation of the pupil center. For each point, a detailed estimation of the iris boundaries is computed, and the final description of the iris boundaries is obtained by merging all the obtained descriptions. The two methods were tested using CASIA v.3 and UBIRIS v.2 images. Experiments show that the proposed approaches are feasible, also in eye images taken in noisy or non-ideal conditions, achieving a total error segmentation accuracy up to 97%.
{"title":"Agent-based image iris segmentation and multiple views boundary refining","authors":"R. D. Labati, V. Piuri, F. Scotti","doi":"10.1109/BTAS.2009.5339077","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339077","url":null,"abstract":"The paper presents two different methods to deal with the problem of iris segmentation: an agent-based method capable to localize the center of the pupil and a method to process the iris boundaries by a multiple views approach. In the first method, an agent corresponds to the coordinates of a specific point of analysis in the input image. A population of agents is deployed in the input image, then, each agent collects local information concerning the intensity patterns visible in its region of interest. By iterations, an agent changes its position accordingly to the local properties, moving towards the estimation of the pupil center. If no available information is present in its region of interest, the agent will move itself along a random walk. After few iterations, the population tends to spread and then concentrate in the inner portion of the pupil. Once the center of the pupil has been located, the inner and outer iris boundaries are refined by an approach based on multiple views analysis. This method starts with a set of points that can be considered as an approximation of the pupil center. For each point, a detailed estimation of the iris boundaries is computed, and the final description of the iris boundaries is obtained by merging all the obtained descriptions. The two methods were tested using CASIA v.3 and UBIRIS v.2 images. Experiments show that the proposed approaches are feasible, also in eye images taken in noisy or non-ideal conditions, achieving a total error segmentation accuracy up to 97%.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128677154","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 : 2009-09-28DOI: 10.1109/BTAS.2009.5339018
Kai Cao, Xin Yang, Xunqiang Tao, Yangyang Zhang, Jie Tian
At present, one of the most challenging problems in fingerprint recognition is the matching of distorted fingerprints. In this paper, we propose penalized quadratic model to deal with the non-linear distortion. Firstly, minutiae as well as sampling points on all the ridges are employed to represent fingerprint. Secondly, similarity between minutiae is estimated by their neighboring sampling points. Thirdly, greedy matching algorithm is adopted to establish the initial minutiae correspondences which are used to select landmarks to calculate the quadratic model parameters. At last, input fingerprint is warped and matching process is conducted again to obtain similarity score between warped fingerprint and template fingerprint. In order to diminish the impact of the erroneous landmarks, we introduce a penalty term into the quadratic model to keep it smoothing. Experimental results on FVC2004 DB1 approve that quadratic model is effective to describe the inner-image transformation of a quadratic skin surface, and the proposed strategy can improve the performance of fingerprint matching algorithm.
{"title":"A novel matching algorithm for distorted fingerprints based on penalized quadratic model","authors":"Kai Cao, Xin Yang, Xunqiang Tao, Yangyang Zhang, Jie Tian","doi":"10.1109/BTAS.2009.5339018","DOIUrl":"https://doi.org/10.1109/BTAS.2009.5339018","url":null,"abstract":"At present, one of the most challenging problems in fingerprint recognition is the matching of distorted fingerprints. In this paper, we propose penalized quadratic model to deal with the non-linear distortion. Firstly, minutiae as well as sampling points on all the ridges are employed to represent fingerprint. Secondly, similarity between minutiae is estimated by their neighboring sampling points. Thirdly, greedy matching algorithm is adopted to establish the initial minutiae correspondences which are used to select landmarks to calculate the quadratic model parameters. At last, input fingerprint is warped and matching process is conducted again to obtain similarity score between warped fingerprint and template fingerprint. In order to diminish the impact of the erroneous landmarks, we introduce a penalty term into the quadratic model to keep it smoothing. Experimental results on FVC2004 DB1 approve that quadratic model is effective to describe the inner-image transformation of a quadratic skin surface, and the proposed strategy can improve the performance of fingerprint matching algorithm.","PeriodicalId":325900,"journal":{"name":"2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129089006","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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