5 Days Course
Advanced Pattern Recognition Techniques for Biometrics
Under the aegis of MHRD - Global Initiative of Academic Networks (GIAN)
March 5 - 9, 2018
How to reach IIT Indore

Authentication of a person to ascertain his/her identity is an important problem in the society. There are three common ways to perform authentication. First one relies on what a person possesses such as keys, identity cards etc. while second one is based on what a person knows such as passwords, personal identification numbers (PINs) etc. Third way of authentication relies on what a person carries, i.e. the unique characteristics of a human being (Biometrics). Even though the first two methods are well established and accepted in the society, they may fail to make true authentication in many occasions. For example, there is a possibility that items under possession may be lost, misplaced or stolen. Similarly one may forget passwords etc. As a result, authentication may not be correct. However, this is not true in case of biometrics. Thus, most of the limitations of traditional ways of authentication which are based on possession and knowledge can be overcome by the use of biometrics. Since it uses characteristics of a person's own body or behavior which he/she always carries, there is no chance of forgetting or losing it. Moreover, body characteristics used for authentication are much more complicated and difficult to forge as compared to remembering a string (such as password) of very long size. The main motivation behind the use of biometrics is to provide a convenient mechanism for person authentication with the help of biological or behavioral characteristics and to eliminate the use of much inconvenient ways of authentication such as the one which are based on ID card, password, physical keys, PINs etc.

There are two types of characteristics which are used in biometrics for person authentication. First type of characteristics is of physiological nature while other ones are based on behavior of human beings. Physiological characteristics depend on "what we have" and derives from the structural information of the human body whereas behavioral characteristics are based on "what we do" and depend on the behavior of a person. The unique biometric characteristic (be it physiological or behavioral) which is used for authentication is commonly referred as a biometric trait. Common examples of physiological biometric traits are face, ear, iris, fingerprint, hand geometry, hand vein pattern, palm print etc. whereas signature, gait (walking pattern), speech, key strokes dynamics etc. are the examples of behavioral biometrics.Biometric recognition uses techniques from Pattern Recognition for performing various tasks such as data preprocessing, feature extraction, feature selection, pattern classification, clustering, and so on. Methods and applications of pattern recognition in biometrics have seen tremendous advances in recent years. This course on Advanced Pattern Recognition Techniques for Biometrics will provide an excellent opportunity to students, researchers and practitioners to learn advanced pattern recognition techniques for biometric recognition.

Objectives of the course
Main objectives of the proposed course are listed below :
  • It will introduce participants to the exciting area of biometric recognition.
  • It will provide participants an opportunity to learn basic as well as advance topics of pattern recognition used in biometrics.
  • The course will deal with both theoretical and practical aspects of pattern recognition techniques for biometrics.
  • It will cover various techniques/algorithms used for feature extraction and matching in biometric recognition.
Topics Covered
  • Introduction to Biometrics: overview of biometrics, common biometric traits, basic biometric system errors, discussion on how to select a biometrics Human vision and image understanding: early neural processing of image structure in the retina, high-level visual attention, representations of image information, extraction of 3D scene information from 2D images, discussion on some exciting evolving application areas of computer vision.
  • Digital acquisition and processing of Biometric data: image: acquisition techniques, 2D and 3D image acquisition, visible and thermal infrared imagery, pre-processing techniques for biometric data Feature extraction and classification: significance of image features, feature selection, feature learning, binary classification , multii-class classification
  • Error rates and normalization: verification and identification performance: computation of various error rates such as FAR, FRR and EER for biometric systems, ROC curve, CMC curve, techniques for feature normalization Fingerprint analysis and recognition: fingerprint sensing, fingerprint representation, matching, fingerprint classification and indexing.
  • Face analysis and recognition: Iris analysis and recognition: data acquisition for face and iris recognition, face and iris recognition techniques, local and global models of feature extraction and matching for face and iris.
  • Soft biometrics and Multi-biometrics: overview, discussion on various sources of biometric information, different levels of fusion, role of ancillary information such as biometric data quality and soft biometric traits (such as height) in performance enhancement , open challenges in multibiometric system design.
Schedule of the Course

Date : March 5-9, 2018
Total Number of days/lectures : 5 days /8 lectures & tutorials

Who Can Attend The Course?
  • Research scholars, graduate students, researchers from different organization across the country working in the area of pattern recognition and biometrics.
  • Young researchers working in R & D laboratories related to pattern recognition and biometrics.
  • Faculty members and academicians interested in the field of pattern recognition and biometrics.
  • Student of all levels (BTech/MSc/MTech/PhD) from academic institutions and technical institutions.
Registration Fee


Early Registration
(on or before January 15, 2018)
Late Registration
(on or before February 10, 2018)
February 10, 2018 or onsite
Participant from outside India
USD 300
USD 400
USD 450
Participant from Industry/ Business organization
Rs. 15,000
Rs. 18,000
Rs. 20,000
Participant from Academic Institution
Rs. 3,500
Rs. 4,500
Rs. 5,000

The fee includes all instructional materials, computer use for tutorials, and lunch. The participants will be provided with single bedded accommodation on payment basis.

How to Apply?

To apply for the course, please follow the steps given below :

Step 1: Payment of Registration Fee:
Payment for the registration fee can be made through online/offline mode. Online payment can be made through NEFT transfer and offline payment can be made through Demand Draft. Details regarding payment are as follows:

I. By Demand Draft : Demand Draft should be drawn in favor of “Registrar, IIT Indore”, payable at Indore.

II. By NEFT Transfer : Registration fee can be paid through NEFT. Transfer of the amount can be done to the account number given below:

Name of the Beneficiary : Registrar, Indian Institute of Technology Indore
Name of Bank : Canara Bank
Branch Code : IIT Indore, Simrol Campus Branch
Beneficiary Account No. : 1476101027440
Bank MICR Code : 452015003
Bank IFS Code : CNRB0006223

Step 2: Registration : After completing the payment of registration fee, fill the application form available http://gian.iiti.ac.in/register.php to complete the registration.

If payment is made through Demand Draft, send your Demand Draft to the following address (also e-mail the scanned copy of the Demand Draft to surya@iiti.ac.in):

Dr. Surya Prakash
Assistant Professor
Research Group on Biometrics, Pattern Recog. & Computer Vision
Discipline of Computer Science and Engineering
Indian Institute of Technology Indore
Simrol Campus, Khandwa Road,
Indore – 453552, India.

Registration can also be done offline by filling the form printed in the brochure (available here) and sending it along with Demand Draft (print of the online payment receipt if payment is made online) to above mentioned address

Faculty Information

Prof. Massimo Tistarelli was born on November 11, 1962 in Genoa, Italy. He is currently a full professor of computer science at the University of Sassari, Italy. He is also the director of the Computer Vision Laboratory at the University of Sassari, Italy.Since 1986 Prof. Massimo Tistarelli has been involved as coordinator, principal investigator and task manager in various projects in the area of on &computer vision and biometrics funded by the European Community. During 1986, 1991 and 1996 he has been visiting the Department of Computer Science, Trinity College, Dublin Ireland.In 1989 he was a visiting scientist at Thinking Machines and the MIT Cambridge, Massachusetts. Main research interests of Prof. Massimo Tistarelli cover biological and artificial vision, biometrics, robotic navigation and visuo-motor coordination. He is an author of more than 100 scientific papers in reputed conferences and international journals. Prof. Tistarelli is the principal editor for the Springer book "Handbook of Remote Biometrics", published in June 2009. In 1991 he was awarded the best paper award from IEEE Computer Society. Since 2000 he has been the chairman for several International workshops on biometrics. Prof. Massimo Tistarelli was the chairman of the 5th IEEE AutoId conference, track chair for biometrics at the 19th ICPR, Area chair for CVPR 2010 and general chair of the IEEE/IAPR 3rd Int.l Conference on Biometrics held in June 2009. He is an associate editor for many reputed journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Image and Vision Computing, IAPR Pattern Recognition, IAPR Pattern Recognition Letters and IET Biometrics.Since 2003 he is the director for the Int.l Summer School on Biometrics (now at the 14th edition). He is the vice-chair of the steering committee for the newly established IAPR Technical Committee 4 on Biometrics, Fellow member of IAPR and senior member of IEEE. Prof. Massimo Tistarelli is a member of the program committee ofseveral international conferences on pattern recognition and image understanding. For more information please visit:https://en.uniss.it/ugov/person/3432

Dr. Surya Prakash is currently an Assistant Professor in Discipline of Computer Science and Engineering at Indian Institute of Technology Indore, India. He is also the Head of discipline of computer science and engineering. He received his MS and PhD degrees in computer science and engineering from Indian Institute of Technology Madras, India and Indian Institute of Technology Kanpur,India respectively. His research interest includes Image processing, computer vision, pattern recognition, biometrics, and identity and infrastructure management. He has published several research articles in peer-reviewed international journals and conferences. He has also co-authored two books titled "IT Infrastructure and Its Management" published by Tata McGraw-Hill, India and "Ear Biometrics in 2D and 3D: Localization and Recognition" published by Springer. He has also been in the program committees of several international conferences in the field of pattern recognition, image processing and intelligent computing. For more information please visit: http://iiti.ac.in/people/~surya/