ForSe Overview Forensics and Security Laboratory (ForSe Lab) School of Computer Engineering Nanyang Technological University.

ForSe Overview

Forensics and Security Laboratory (ForSe Lab)

School of Computer EngineeringNanyang Technological University

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Mission of ForSe Lab To create a synergistic group dedicated to research

in the application of computational techniques to biometrics, information security and forensic

analysis.

To perform cutting edge research and train and develop talents to support Singapore’s efforts in the areas of Homeland Security and Infocomm Security.

To make use of strong research base to further enhance the research contributions from NTU to the

international arena in the areas of forensic and security.

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Vision of ForSe lab To be one of the major research

labs/centres for research and development in the areas of forensics, biometrics, and

security technologies.

To be a strong research arm between academic and industry to support R&D activities in forensics and security for

Singapore.

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Facts and Figures

Established in late 2005. 6 active faculty members, 1 research

assistant, 1 lab executive, 11 PhD students.

6 funded projects with total amount over S$500K.

Supports approximately 10-15 Final Year Projects every academic year

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Research Funding Award

InfoComm Research cluster, NTU

Institute for Infocomm Research (I2R) – Joint Collaboration Project with I2R

Three Academic Research Fund Tier 1, Ministry of Education, Singapore

MINDEF-NTU Joint R&D project

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Active Members

David Cho (Asst Prof)Director

Maylor Leung(Assoc Prof)

Vinod Prasad (Asst Prof)

Adams Kong(Asst Prof)

Sudha Natarajan (Asst Prof)

Li Fang (Lecturer)

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Our Knowledge/Expertise

Pattern Recognition Machine Learning Digital Signal Processing Image Processing Embedded System Information Security Software Engineering

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Research Focused AreasForensics and Security Lab

Forensic AnalysisBiometrics and

SecurityInformation

Security

Forensic ana lysis o fd ig ita l evidenceim ages

Forensic ana lysis o fspeaker vo ice

Forensic ana lysis o fim age fo rgery

Forensic exam inationof d ig ita l devices

H and and Facia lTherm al pa tte rnana lysis

P a lm prin t, Face, Irisand E ar recogn ition

H um an actionana lysis fo r videosurve illance

S m art h idden weapondetection

D igita l C ontentP ro tection

D igita l C rim e SceneR econstruction

T ra ffic F lowM onitoring andM odeling

H um an B ehaviorA na lysis

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Key Contributions – Forensic Analysis

Hand Vein Pattern Analysis

Speaker Identification Acoustic Voice Feature

Image Forgery Detection

Skin and/or Hair Analysis

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Key Contributions – Biometrics Technology Facial Thermal pattern analysis

Palmprint recognition

Face recognition

Iris recognition

Ear recognition

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Key Contributions – Security Engineering

An Embedded Camera System for Vision Based Surveillance

Hidden Weapon Detection

Human behaviour and brain analysis EEG Signal Analysis Emotion Recognition

ConfigurablePreprocessing

ArchitectureCamera

Vision-basedsurveillanceframew ork

SmartEye system

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Future Plans in ForSe Lab To extend and build more research activities with

the research areas of the lab to attract external funding.

To focus our staffs to prepare and submit major research proposals to several funding agencies, such as, AcRF, A-Star, DSTA, DSO,…etc.

To collaborate with other major organizations, such as, I2R, Singapore Police Force, MHA and also some companies in security industry, …etc.

To continue our excellent tradition of publishing our new discoveries and theories in renowned journals, conferences,…etc.

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Collaborators International

Prof. Graham Leedham, Dean of School, University of New England, Australia

Prof. M. Kamel, IEEE Fellow, University of Waterloo, Canada Dr. Noah Caft, MD, PhD, Assistant Professor, UCAL, USA Prof. D. Zhang, IEEE Fellow, The Hong Kong Polytechnic

University, HK Prof. Tommy Chow, City University of Hong Kong

Local Dr. Li Haizhou, Dr Guan Cuntai and Dr. Vladimir Pervouchine,

Institute of Infocomm Research (I2R) Dr. TAY Ming Kiong Michael , Director, Physical Evidence Division,

Applied Sciences Group Ms. LIM Chin Chin, Head, Criminalistics Laboratory, Centre for

Forensic Science Dr. LOH Tsee Foong, MD, Head and Senior Consultant, KK

Women’s and Children’s Hospital Dr. James Wong (Application Architect), PCS Security Pte Ltd

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Recent Publication L. Wang, G. Leedham and Siu-Yeung Cho, "Minutiae Feature Analysis for

Infrared Hand Vein Pattern Biometrics", Pattern Recognition (JCR impact factor: 3.279), 41 (3), pp. 920-929, 2008.

Lingyu Wang, Graham Leedham and Siu-Yeung Cho, “A Physiological Vein Pattern Biometric System”, HKIE Transactions, vol. 15, iss. 4, Dec. 2008 (shortlisted paper for The HKIE Outstanding Paper Award for Young Engineers/Researchers 2008).

L. Wang, G. Leedham and S.-Y. Cho, "Infrared imaging of hand vein patterns for biometric purposes", IET Computer Vision (JCR impact factor: 0.667), vol. 1, Iss. 3-4, pp. 113-122, Dec. 2007.

Siu-Yeung Cho, Lingyu Wang and Wen Jin Ong, “Thermal Imprint Feature Analysis for Face Recognition”, in IEEE International Symposium on Industrial Electronics 2009, July 2009, Seoul, Korea.

Haishan Zhong, Siu-Yeung (David) Cho, Vladimir Pervouchine, Graham Leedham, “Combining Novel Acoustic Features using SVM to Detect Speaker Changing Points”, BIOSIGNALS (1) 2008: 224-227.

N.B. Puhan and N. Sudha, "A novel iris database indexing method using the iris color", Proceedings of the IEEE International Conference on Industrial Electronics and Applications, Singapore, June 2008.

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Thank you!

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Hand-vein pattern analysis A vein pattern refers to the vast network of blood vessels

underneath the skin of a certain part of a person’s body Images captured in an air-conditioned office environment (20-25°C

and <50% humidity)

FIR Image of Back of hand imaged in a normal office environment – major veins are clearly visible

NIR images of the palms of two hands

NIR images of the back of the hand (left) and the wrist (right)

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Hand-vein pattern analysis

We have proposed a system that recognizes the human hand vein pattern images acquired by both far and near-infrared camera, which consists of five individual stages

ImageAcquisition

Vein PatternSegmentation

Skeletonization ShapeMatch

DecisionRaw Raw ImagesImages

FinerFinerImagesImages

Database

Vein Vein PatternPattern

TemplateTemplate

ImageEnhancement& ROI Selection

Data Collection Vein Pattern Extraction

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Results

Skeleton and Minutiae Points of the Vein Pattern

Error Rate Curves for Minutiae Recognition Using the Modified Hausdorff Distance (EER=7.5% when the threshold is set to 25)

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Image Forgery Detection With the advent of low-cost and high-resolution

digital cameras, and sophisticated photo editing software, digital images can be easily manipulated and altered. create forgeries, which are indistinguishable by

naked eye

(a) Real image; (b) Forged version; (c) Duplicated regions Return

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Skin Analysis

Skin marking system Data collection system

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Principles of Thermal Facial Patterns for Biometrics The convective heat transfer from the flow of warm arterial

blood in superficial vessels is at a temperature gradient against the cooler surrounding tissue

Creating a characteristic thermal imprint on our face This thermal pattern provides an alternative feature sets in

addition to those visible features for face recognition

P. Buddharaju,et. al, “Physiology-Based face Recognition in the Thermal Infrared Spectrum”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29 no.4, pp. 613-626, April 2007.

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Database Data Collection

Thermal face images can be formed by capturing the temperature profile by the NEC TH9100SL thermal camera

Grayscale images with a resolution of 320x240 are used.

Database provided by Equinox Corporation. Frontal thermal face dataset 300 images from 30 different subjects (10 images for

each subjects).

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Face Segmentation

(b) Edge detection with small objects removed

(c) Centre portion of the image is flood filled

(d) Difference Image (f) Contrast adjusted

(a) Image after enhancement

(e) Mask is multiplied with the image

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Extracting Thermal Minutiae Points

Use morphological top-hat operation to obtain the critical edge map

Then extract the minutiae points by the cross numbering concept.

(a) Thermal face region (b) Critical edge map (c) Minutiae points

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Matching the Aligned TMPs

Using the same MHD measurement Achieved 6.7% EER

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Ear Recognition Rationale:

Earmarks can be used as a biometric, but a computerized system for earmarks identification does not existed.

The structure of the ear does not change radically over time, especially after the first four months of birth.

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Ear Recognition Current work:

Build a ear profile database of 38 individuals (will be extended the number later)

Implement an automatic ear detection, localization and recognition system

A 11% Equal-Error-Rate is achieved.

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Concealed Weapon Detection Objective: to find out the feasibility of software based

image processing techniques in detecting concealed weapons with infrared (IR) thermal imager without violating the privacy of the people involved.

Visible image IR image Fused IR image

NEC Thermo Tracer

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Concealed Weapon Detection

On-going works: Fuzzy clustering of IR images Advanced image registration methods Intelligent and decision based image fusion Robust shape matching Collaborating with EEE staffs to work with IR and MMW

image sensing

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Human behaviour and brain analysis – Emotion Recognition

Potential applications:• Lie detection for forensics• Crime investigation• Understanding Criminal Psychology

Typical real-time facial expression system

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