1. 1. Head of department -Sabina Ansari Case study teacher -Priyanka pawar LAXMAN DEVRAM SONAWANE COLLEGE
2. 2. Case study on Face recognition in e-attendance
3. 3. Overview Introduction History What are biometrics Why we choose face recognition over other biometrics What is face recognition Components of face recognition How facial recognition system works Where face recognition technology is used Future of face recognition
4. 4. Introduction In today's networked world, the need to maintain the security of information or physical property is becoming both increasingly important and increasingly difficult. Face recognition is one of the few biometric methods that possess the merits of both high accuracy & Complex and largely software based technique. Analyze unique shape, pattern & positioning of facial features. It compare scans to records stored in central or local database or even on a smart card.
5. 5. History The first attempts to use face recognition began in the 1960s with a semi-automated system. Marks were made on photographs to locate the major features; it used features such as eyes, ears, noses, and mouths. Then distances and ratios were computed from these marks to a common reference point and compared to reference data. In 1970s, Goldstein and Harmon used 21 specific subjective markers such as hair color and lip thickness to automate the recognition. This proved even harder to automate due to the subjective nature of many of the measurements still made completely by hand.
6. 6. What are biometrics A biometric is a unique, measurable characteristic of a human being that Can be used to automatically recognize an individual or verify an individuals identity.
7. 7. Biometrics can measure both physiological and behavioral characteristics Physiological biometrics:- This types of biometrics is based on measurements and data derived from direct measurement of a part of the human body. Behavioral biometrics:- This types of biometrics is based on measurements and data derived from an action.
8. 8. Types of biometrics PHYSIOLOGICAL BEHAVIORAL Finger-scan Voice-scan Facial Recognition Signature-scan Iris-scan Keystroke-scan Retina-scan Hand-scan
9. 9. Why we choose face recognition over other biometrics It requires no physical interaction on behalf of user. It is accurate and allows for high enrolment and verification. Not require an expert to interpret the comparison result. It can use your existing hardware infrastructure, existing cameras and image capture, devices will work with no problems. It is the only biometric that allow you to perform passive identification in one to Many environments (e.g.: identifying a terrorist in a busy Airport terminal.
10. 10. What is face recognition Face recognition is one of the few biometric methods that possess the merits of both high accuracy and low intrusiveness. A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image from the source, One of the ways to do this is by comparing selected facial features from the image and a facial database.
11. 11. Detection two-class classification. Face vs. Non-face. Recognition multi-class classification. One person vs. all the others. Difference between face detection and recognition
12. 12. Two types of comparison in face recognition Face Verification: The system compares a face image that might not belong to the database, verify whether it is from the person it is claimed to be in the database. Face Identification: The system compares a face image that belongs to a person in a database, tell whose image it is.
13. 13. Stages of identification Capture Extraction Comparison Match/Non match Accept/Project 1 2 3 4 5 Capture- Capture the behavioral and physical sample. Extraction- Unique data is extracted from the sample and a template is created. Comparison- The template is compared with a new sample. Match/non match- The system decides whether the new samples are matched or not.
14. 14. Components of face recognition Enrollment module-An automated mechanism that scans and captures a digital or analog image of a living personal characteristics. Database-Another entity which handles compression ,processing ,data storage and compression of the captured data with stored data. Identification module-The third interfaces with the application system.
15. 15. How facial recognition system works Facial recognition software is based on the ability to first recognize faces, which is a technological feat in itself. If you look at the mirror, you can see that your face has certain distinguishable landmarks. These are the peaks and valleys that make up the different facial features. VISIONICS defines these landmarks as nodal points. There are about 80 nodal points on a human face.
16. 16. distance between the eyes width of the nose depth of the eye socket cheekbones jaw line Nodal points that are measured by the software
17. 17. Detection- when the system is attached to a video surveillance system, the recognition software searches the field of view of a video camera for faces. If there is a face in the view, it is detected within a fraction of a second. A multi-scale algorithm is used to search for faces in low resolution. The system switches to a high- resolution search only after a head-like shape is detected. Alignment- Once a face is detected, the system determines the head's position, size and pose. A face needs to be turned at least 35 degrees toward the camera for the system to register it. Normalization-The image of the head is scaled and rotated so that it can be registered and mapped into an appropriate size and pose. Normalization is performed regardless of the head's location and distance from the camera. Light does not impact the normalization process.
18. 18. Representation-The system translates the facial data into a unique code. This coding process allows for easier comparison of the newly acquired facial data to stored facial data. Matching- The newly acquired facial data is compared to the stored data and (ideally) linked to at least one stored facial representation.
19. 19. Advantages and disadvantages ADVANTAGES Convenient, social acceptability. More user friendly. Inexpensive technique of identification. DISADVANTAGES Problem with false rejection when people change their hair style, grow or shave a beard or wear glasses. Face recognition systems cant tell the difference between identical twins.
20. 20. Where face recognition technology is used Airports and railway stations Voter verification Cashpoints Stadiums Public transportation Financial institutions Government offices Businesses of all kinds
21. 21. Future of face recognition Some consider the problem impossible. Advancements in hardware and software. Slow integration into society in limited environments. Very large potential market.
22. 22. CONCLUSION Face recognition technologies have been associated generally with very costly top secure applications. Today the core technologies have evolved and the cost of equipment's is going down dramatically due to the integration and the increasing processing power. Certain applications of face recognition technology are now cost effective, reliable and highly accurate. As a result there are no technological or financial barriers for stepping from pilot project to widespread deployment. For implementations where the biometric system must verify and identify users reliably over time, facial scan can be a very difficult, but not impossible, technology to implement successfully.
23. 23. Thanks