Algorithms and VLSI Architectures for Low-Power Mobile Face Verification

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THSE PRSENTE LA FACULT DES SCIENCES POUR L OBTENTION DU GRADE DE DOCTEUR S SCIENCES

Algorithms and VLSI Architectures for Low-Power Mobile Face Verificationpar Jean-Luc Nagel

Accepte sur proposition du jury: Prof. F. Pellandini, directeur de thse PD Dr. M. Ansorge, co-directeur de thse Prof. P.-A. Farine, rapporteur Dr. C. Piguet, rapporteur Soutenue le 2 juin 2005

I NSTITUT DE M ICROTECHNIQUE U NIVERSIT DE N EUCHTEL 2006

To the best of my knowledge and belief, this thesis contains no material previously published or communicated by another person, that has not been duly referred to in the course of the manuscript. Copyright 2006 by Jean-Luc Nagel and IMT-UniNE Dissertation typeset with Adobe FrameMaker 6.0 by the author.

A mes parents

KeywordsBiometrics; face authentication; image acquisition and processing; pattern recognition; mobile devices; low-power digital circuits and systems design.

AbstractAmong the biometric modalities suitable for mobile applications, face verification is definitely an interesting one, because of its low level of invasiveness, and because it is easily applicable from the user viewpoint. Additionally, a reduced cost of the identity verification device is possible when sharing the imaging device between different applications. This is for instance not possible with fingerprint verification, which asks for a specific sensor. This Ph.D. thesis addresses the problem of conceiving a low-power face authentication system adapted to the stringent requirements of mobile communicators, including the study and design of the algorithms, and the mixed hardware and software implementation on a dedicated multi-processors platform. With respect to the anterior state-of-art, this thesis proposes several original algorithmic improvements, and an original architecture for a VLSI System-On-Chip realization, where the algorithmic and architectural aspects have been jointly optimized, so as to enable the execution of the face verification to be entirely processed on low-power mobile devices such as mobile phones, or personal digital assistants. At the time when this work was undertaken and completed, there were no similar results published either from the academic scientific community, or from the market in form of a product description / announcement. The mobile environment is known to be characterized by large variations in image acquisition conditions with regard to the scene acquisition viewpoint and illumination, and it is therefore requiring a sound optimization of the algorithmic robustness. Moreover, face verification is a quite complex task that is usually performed on powerful - possibly

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multi-processor - mainframe computers rather than on low-power digital signal processors. In the case of mobile applications, the algorithms need to be tightly optimized, and specific hardware architectures need to be developed in order to fulfill the power consumption constraints. This thesis thus embraces several domains such as cognitive science, pattern recognition, image acquisition and processing, and low-power digital circuit design. The first part of the thesis presents a list of possible applications and of constraints raised by the mobile environment, and an extensive literature review. A class of algorithms is selected, characterized, and optimized with respect to the specificities of mobile face verification. The second part of the thesis describes a System-onChip implementation performed at system-level, including image acquisition and higher-level processing. Finally, the architecture of a specific embedded VLSI coprocessor is described and discussed complementarily to the corresponding design methodology used.

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Mots-clsBiomtrie; vrification de visages; acquisition et traitement dimage; reconnaissance de formes; terminaux mobiles; conception de circuits et sytmes numriques faible consommation.

RsumParmi les modalits biomtriques convenant la vrification didentit sur un dispositif portable, la reconnaissance de visage est particulirement intressante de par sa faible invasivit, et de par sa simplicit dusage (du moins du point de vue de lutilisateur). De plus, le cot du dispositif de vrification didentit peut tre rduit lorsque le senseur dimage est partag entre plusieurs applications. Ce nest pas le cas de la reconnaissance dempreintes digitales, par exemple, qui ncessite un senseur propre. Cette thse traite le problme de la conception dun sysme de vrification de visage faible consommation, adapt aux besoins pointus des terminaux mobiles. Ce travail comprend ltude et la conception dalgorithmes, ainsi quune implantation mixte matriellelogicielle sur une plate-forme ddie comprenant plusieurs processeurs. Par rapport ltat de lart, cette thse propose plusieurs amliorations algorithmiques originales, et une architecture VLSI originale pour la ralisation dun systme sur puce, dans laquelle les aspects algorithmiques et architecturaux ont t conjointement optimiss, de sorte que lexcution de la reconnaissance de visage peut tre entirement traite sur le dispositif mobile (tlphone portable ou un agenda personnel). Au moment de la ralisation et de la clture de ce travail de thse, aucun rsultat quivalent navait t publi par la communaut scientifique, ou ntait disponible sur le march sous la forme dune description ou annonce de produit. Lenvironnement mobile est caractris par de larges variations des conditions dacquisition des images, en ce qui concerne langle de vue et lillumination, ce qui ncessite une consquente optimisation de la

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robustesse des algorithmes. De plus, la vrification de visages est une tche relativement complexe, gnralement effectue sur des stations comportant un ou plusieurs processeurs performants, plutt que sur des processeurs de traitement du signal faible consommation. Dans le cas des applications portables, les algorithmes doivent donc tre galement optimiss en termes de complexit, et des architectures matrielles spcialises doivent tre dveloppes pour arriver respecter les contraintes de consommation lectrique. Cette thse couvre donc diffrents domaines, tels que les sciences cognitives, la reconnaissance de formes, lacquisition et le traitement dimage, et la conception de circuits intgrs numriques faible consommation. La premire partie du rapport dcrit une liste dapplications possibles, et les contraintes imposes par lenvironnement mobile, ainsi quune revue de ltat de lart tendue. Une catgorie dalgorithmes est slectionne, caractrise, et optimise en fonction des spcificits de la vrification didentit sur un appareil portable. La deuxime partie de la thse dcrit au niveau systme une implantation sous la forme dun systme-sur-puce contenant aussi bien le senseur dimage quun micro-contrleur et des blocs de traitement spcialiss (coprocesseurs). Finalement, une architecture spcifique de coprocesseur embarqu est dcrite et discute, complmentairement la mthodologie de conception utilise.

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ContentsAbstract Rsum Chapter 1: Introduction 1.1 Motivations 1.2 Organization of the thesis 1.3 Contributions Chapter 2: Biometrics 2.1 Introduction 2.2 Biometric modalities2.2.1 2.2.2 2.2.3 2.2.4 2.2.5 2.2.6 2.2.7 Hand geometry Retina Iris Voice Fingerprint Face Others

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1 2 2

5 88 9 9 10 10 11 12

2.3 2.4 2.5 2.6 2.7

Verification vs. identification Applications of biometrics Mobile applications of biometric authentication Privacy Performance evaluation of biometric systemsDefinitions Technology evaluation Scenario evaluation

12 13 14 17 1820 21 27

2.7.1 2.7.2 2.7.3

2.8 Conclusion References Chapter 3: State-of-art in Face Recognition 3.1 Introduction 3.2 From cognitive to computer science

28 30

33 34 xi

3.2.1 3.2.2 3.3.1 3.4.1 3.4.2 3.4.3 3.4.4 3.4.5 3.4.6

Face recognition: a cognitive process Face recognition: a computational process Determination of algorithm selection criteria Feature-based methods Template-based methods Eigenface-based methods Local feature analysis methods Graph -based methods Other approaches

34 39

3.3 Classification of computational methods 3.4 Non-exhaustive review of algorithms for face recognition

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4546 49 50 56 58 62

3.5 Summary and algorithm selection 3.6 Projects consortia, commercial products and patents 3.7 Conclusion References Chapter 4: Elastic Graph Matching Algorithm Applied to Face Verification 4.1 Algorithm architecture 4.2 Image normalization4.2.1 4.2.2 4.3.1 4.3.2 4.3.3 4.3.4 4.4.1 4.4.2 4.4.3 4.5.1 4.5.2 4.5.3 Effects of illumination variations Illuminant normalization techniques Gabor transform-based features Discrete cosine transform-based features Mathematical morphology based features Normalized mathematical morphology based features Principal component analysis Linear discriminant analysis Node weighting Rigid matching using iterative methods Elastic matching using physical models Elastic matching using statistical models

62 66 75 76

84 8586 95

4.3 Feature extraction

100102 118 121 123

4.4 Feature space reduction

132132 139 141

4.5 Graph matching

142143 148 152

4.6 Classifiers and decision theory 4.7 Performance evaluation4.7.1 4.7.2 XM2VTS database Yale B database

153 157157 159

4.8 Conclusion References

160 162

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Chapter 5: Further Use of Elastic Graph Matching 5.1 Face detection5.1.1 5.1.2 5.2.1 5.2.2 5.2.3 5.2.4 5.2.5 Color-based method Model-based method Requirements for mobile applications Brief review of existing algorithms Proposed algorithm based on EGM Performance evaluation Further possible improvements

167169 173

5.2 Fingerprint verification

178178 182 183 189 191

5.3 Conclusion References 6.1 Introduction 6.2 Low-power desi

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