Face recognition application
- 2. Outline 1. Introduction 2. Biometrics 3. Facial Recognition 4. Implementation 5. How it works 6. System Requirement 7. Applications 8. Screenshots 9. Conclusion 10. References
- 3. Introduction Everyday actions are increasingly being handled electronically, instead of pencil and paper or face to face. This growth in electronic transactions results in great demand for fast and accurate user identification and authentication. Access codes for buildings, banks accounts and computer systems often use PIN's for identification and security clearances. Using the proper PIN gains access, but the user of the PIN is not verified. When credit and ATM cards are lost or stolen, an unauthorized user can often come up with the correct personal codes. Face recognition technology may solve this problem since a face is undeniably connected to its owner expect in the case of identical twins.
- 4. Biometric A biometric is a unique, measurable characteristic of human being that can be used to automatically recognize an individual or verify an individual's identity. Biometrics can measure both physiological and behavioral characteristics. Physiological biometrics : - This biometrics is based on measurements and data derived from direct measurement of a part of the human body. Behavioral biometrics : - This biometrics is based on measurements and data derived from an action.
- 5. Type Of Biometric Physiological a. Finger-scan b. Facial Recognition c. Iris-scan d. Retina-scan e. Hand-scan Behavioral a. Voice-scan b. Signature-scan c. Keystroke-scan
- 6. Face Recognition Facial recognition (or face recognition) is a type of biometric software application that can identify a specific individual in a digital image by analyzing and comparing patterns. Wide availability of powerful and low-cost desktop and embedded computing systems has created an enormous interest in automatic processing of digital images in a variety of applications, including biometric authentication, surveillance, human-computer interaction, and multimedia management. Face recognition is a task that humans perform routinely and effortlessly in our daily lives.
- 7. Implementation The implementation of face recognition technology includes the following stages : Image acquisition Image processing Distinctive characteristic location Template matching Template creation These nodal points are measured creating a numerical code, called a face print, representing the face in the database.
- 8. How Face Recognition Work Face recognition software is based on the ability to first recognize faces, which is a technological feat in itself. If you look at the mirror, we 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. Here are few nodal points that are measured by the software Distance between the eyes Width of the nose Depth of the eye socket Cheekbones Chin
- 9. Model Description Add Image In this we add Image by capturing from web camera and store them in our system. During registration four images are captured. Image Capture Module This module is used to capture image using web camera. This is written as a separate thread to avoid system hanging. This module is used to capture image in login module and registration module. Eigenface Computation This module is used to compute the "face space" used for face recognition. The recognition is actually being carried out in the Face Bundle object, but the preparation of such object requires doing lots of computations. Identification This module contains the functionality to take the image from above module and it compares or searches with the images already there in the database. If any image is matched then a success` message is shown to the user.
- 10. System Requirement Specification Hardware Requirements Processor : Pentium IV Clock Speed : 2.86GHZ Processor Hard disk : 1GB RAM : 64MB Software Requirements Operating System : Window 2000 .NetFrame : v4.5 Front-end Tools : C# Open Libraries : OpenCv
- 11. About OpenCv OpenCv is an Image Processing library created by Intel and maintained by Willow Garage. Available for C, C++, Python and for also another languages. It was Open Source and Free. It is a collection of C functions and a few C++ classes that implement some popular Image Processing and Computer Vision algorithms. Cross-Platform API of C functions FREE for commercial and non-commercial uses Basic OpenCv Structure 1. Point, Point2f - 2D Point 2. Size - 2D size structure 3. Rect - 2D rectangle object 4. RotatedRect - Rect object with angle 5. Mat - image object OpenCv
- 12. Use Case Diagram Capture Photo Character Identification Display Information Alert Notice Alert Notice Review Analyses Static Image Repository Static Image Repository
- 13. Screenshots This module help us to save new image. This module help us to see information about image detected. This use to open webcam. Area of displaying. Main Window
- 14. Conclusion Factors such as environmental changes and mild changes in appearance impact the technology to a greater degree than many expect. 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.
- 15. Reference 1. http://www.opencv.org/ 2. https://msdn.microsoft.com/en-us/library/67ef8sbd.aspx 3. http://www.tutorialspoint.com/csharp/
- 16. Thank You