A dynamically weighted multi-modal biometric security system
- Brown, Dane L, Bradshaw, Karen L
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473684 , vital:77672 , xlink:href="https://www.researchgate.net/publication/315839228_A_Dynamically_Weighted_Multi-Modal_Biometric_Security_System"
- Description: The face, fingerprint and palmprint feature vectors are automatically extracted and dynamically selected for fusion at the feature-level, toward an improved human identification accuracy. The feature-level has a higher potential accuracy than the match score-level. However, leveraging this potential requires a new approach. This work demonstrates a novel dynamic weighting algorithm for improved image-based biometric feature-fusion. A comparison is performed on uni-modal, bi-modal, tri-modal and proposed dynamic approaches. The proposed dynamic approach yields a high genuine acceptance rate of 99.25% genuine acceptance rate at a false acceptance rate of 1% on challenging datasets and big impostor datasets.
- Full Text:
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473684 , vital:77672 , xlink:href="https://www.researchgate.net/publication/315839228_A_Dynamically_Weighted_Multi-Modal_Biometric_Security_System"
- Description: The face, fingerprint and palmprint feature vectors are automatically extracted and dynamically selected for fusion at the feature-level, toward an improved human identification accuracy. The feature-level has a higher potential accuracy than the match score-level. However, leveraging this potential requires a new approach. This work demonstrates a novel dynamic weighting algorithm for improved image-based biometric feature-fusion. A comparison is performed on uni-modal, bi-modal, tri-modal and proposed dynamic approaches. The proposed dynamic approach yields a high genuine acceptance rate of 99.25% genuine acceptance rate at a false acceptance rate of 1% on challenging datasets and big impostor datasets.
- Full Text:
A dynamically weighted multi-modal biometric security system
- Brown, Dane L, Bradshaw, Karen L
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/476629 , vital:77945 , ISBN 9780620724180
- Description: The face, fingerprint and palmprint feature vectors are automatically extracted and dynamically selected for fusion at the feature-level, toward an improved human identification accuracy. The feature-level has a higher potential accuracy than the match score-level. However, leveraging this potential requires a new approach. This work demonstrates a novel dynamic weighting algorithm for improved image-based biometric feature-fusion. A comparison is performed on uni-modal, bi-modal, tri-modal and proposed dynamic approaches. The proposed dynamic approach yields a high genuine acceptance rate of 99.25% genuine acceptance rate at a false acceptance rate of 1% on challenging datasets and big impostor datasets.
- Full Text:
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/476629 , vital:77945 , ISBN 9780620724180
- Description: The face, fingerprint and palmprint feature vectors are automatically extracted and dynamically selected for fusion at the feature-level, toward an improved human identification accuracy. The feature-level has a higher potential accuracy than the match score-level. However, leveraging this potential requires a new approach. This work demonstrates a novel dynamic weighting algorithm for improved image-based biometric feature-fusion. A comparison is performed on uni-modal, bi-modal, tri-modal and proposed dynamic approaches. The proposed dynamic approach yields a high genuine acceptance rate of 99.25% genuine acceptance rate at a false acceptance rate of 1% on challenging datasets and big impostor datasets.
- Full Text:
A multi-biometric feature-fusion framework for improved uni-modal and multi-modal human identification
- Brown, Dane L, Bradshaw, Karen L
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473696 , vital:77673 , xlink:href="https://ieeexplore.ieee.org/abstract/document/7568927"
- Description: The lack of multi-biometric fusion guidelines at the feature-level are addressed in this work. A feature-fusion framework is geared toward improving human identification accuracy for both single and multiple biometrics. The foundation of the framework is the improvement over a state-of-the-art uni-modal biometric verification system, which is extended into a multi-modal identification system. A novel multi-biometric system is thus designed based on the framework, which serves as fusion guidelines for multi-biometric applications that fuse at the feature-level. This framework was applied to the face and fingerprint to achieve a 91.11% recognition accuracy when using only a single training sample. Furthermore, an accuracy of 99.69% was achieved when using five training samples.
- Full Text:
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473696 , vital:77673 , xlink:href="https://ieeexplore.ieee.org/abstract/document/7568927"
- Description: The lack of multi-biometric fusion guidelines at the feature-level are addressed in this work. A feature-fusion framework is geared toward improving human identification accuracy for both single and multiple biometrics. The foundation of the framework is the improvement over a state-of-the-art uni-modal biometric verification system, which is extended into a multi-modal identification system. A novel multi-biometric system is thus designed based on the framework, which serves as fusion guidelines for multi-biometric applications that fuse at the feature-level. This framework was applied to the face and fingerprint to achieve a 91.11% recognition accuracy when using only a single training sample. Furthermore, an accuracy of 99.69% was achieved when using five training samples.
- Full Text:
An investigation of face and fingerprint feature-fusion guidelines
- Brown, Dane L, Bradshaw, Karen L
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473751 , vital:77678 , xlink:href="https://doi.org/10.1007/978-3-319-34099-9_45"
- Description: There are a lack of multi-modal biometric fusion guidelines at the feature-level. This paper investigates face and fingerprint features in the form of their strengths and weaknesses. This serves as a set of guidelines to authors that are planning face and fingerprint feature-fusion applications or aim to extend this into a general framework. The proposed guidelines were applied to the face and fingerprint to achieve a 91.11 % recognition accuracy when using only a single training sample. Furthermore, an accuracy of 99.69 % was achieved when using five training samples.
- Full Text:
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473751 , vital:77678 , xlink:href="https://doi.org/10.1007/978-3-319-34099-9_45"
- Description: There are a lack of multi-modal biometric fusion guidelines at the feature-level. This paper investigates face and fingerprint features in the form of their strengths and weaknesses. This serves as a set of guidelines to authors that are planning face and fingerprint feature-fusion applications or aim to extend this into a general framework. The proposed guidelines were applied to the face and fingerprint to achieve a 91.11 % recognition accuracy when using only a single training sample. Furthermore, an accuracy of 99.69 % was achieved when using five training samples.
- Full Text:
Extended feature-fusion guidelines to improve image-based multi-modal biometrics
- Brown, Dane L, Bradshaw, Karen L
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473796 , vital:77682 , xlink:href="https://doi.org/10.1145/2987491.2987512"
- Description: The feature-level, unlike the match score-level, lacks multi-modal fusion guidelines. This work demonstrates a practical approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature-level for improved human identification accuracy. Feature-fusion guidelines, proposed in recent work, are extended by adding the palmprint modality and the support vector machine classifier. Guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature-level to reduce the equal error rate on the SDUMLA and IITD datasets, using a novel feature-fusion methodology.
- Full Text:
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473796 , vital:77682 , xlink:href="https://doi.org/10.1145/2987491.2987512"
- Description: The feature-level, unlike the match score-level, lacks multi-modal fusion guidelines. This work demonstrates a practical approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature-level for improved human identification accuracy. Feature-fusion guidelines, proposed in recent work, are extended by adding the palmprint modality and the support vector machine classifier. Guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature-level to reduce the equal error rate on the SDUMLA and IITD datasets, using a novel feature-fusion methodology.
- Full Text:
Improved fingercode alignment for accurate and compact fingerprint recognition
- Brown, Dane L, Bradshaw, Karen L
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473807 , vital:77683 , xlink:href="https://ieeexplore.ieee.org/abstract/document/7568931"
- Description: The traditional texture-based fingerprint recognition system known as FingerCode is improved in this work. Texture-based fingerprint recognition methods are generally more accurate than other methods, but at the disadvantage of increased storage requirements. The low storage requirements for a low resolution texture-based fingerprint recognition method known as FingerCode enables the combined use of fingerprints with the additional security of other devices such as smartcards. The low recognition accuracy of FingerCode is addressed using a novel texture alignment technique. As a result, an improved recognition accuracy is achieved without increasing storage requirements.
- Full Text:
- Authors: Brown, Dane L , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/473807 , vital:77683 , xlink:href="https://ieeexplore.ieee.org/abstract/document/7568931"
- Description: The traditional texture-based fingerprint recognition system known as FingerCode is improved in this work. Texture-based fingerprint recognition methods are generally more accurate than other methods, but at the disadvantage of increased storage requirements. The low storage requirements for a low resolution texture-based fingerprint recognition method known as FingerCode enables the combined use of fingerprints with the additional security of other devices such as smartcards. The low recognition accuracy of FingerCode is addressed using a novel texture alignment technique. As a result, an improved recognition accuracy is achieved without increasing storage requirements.
- Full Text:
Towards a technical skills curriculum to supplement traditional computer science teaching
- Marais, Craig, Bradshaw, Karen L
- Authors: Marais, Craig , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/476640 , vital:77946 , ISBN 9781450342315 , https://muse.jhu.edu/book/52741
- Description: It is commonplace for students to enter university with skills deficiencies. However, this is cause for growing concern in the context of South Africa, as these `deficient' students are becoming more numerous. Public secondary schools in South Africa are failing to create students with adequate skills for careers in the STEM fields. This paper isolates these skills deficiencies to a subset of technical skills for problem-solving. The problem-solving skills are divided into content groups, which are then aligned to existing Computer Science content. A solution is proposed that demonstrates how the content can be presented without the need for extensive curriculum changes to established course content.
- Full Text:
- Authors: Marais, Craig , Bradshaw, Karen L
- Date: 2016
- Subjects: To be catalogued
- Language: English
- Type: text , book
- Identifier: http://hdl.handle.net/10962/476640 , vital:77946 , ISBN 9781450342315 , https://muse.jhu.edu/book/52741
- Description: It is commonplace for students to enter university with skills deficiencies. However, this is cause for growing concern in the context of South Africa, as these `deficient' students are becoming more numerous. Public secondary schools in South Africa are failing to create students with adequate skills for careers in the STEM fields. This paper isolates these skills deficiencies to a subset of technical skills for problem-solving. The problem-solving skills are divided into content groups, which are then aligned to existing Computer Science content. A solution is proposed that demonstrates how the content can be presented without the need for extensive curriculum changes to established course content.
- Full Text:
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