Introduction Types of face recognition How it works Working steps Algorithms used Problems faced Future uses Conclusion
Inthe 1960s, scientists began work on using the computer to recognize human faces. Since then, face recognition technology has come a long way.A Face recognition software is based on the ability to recognize a face by measuring the various features of the face.
Every face has numerous distinguishable landmarks,the different peaks and valleys that make facial features. Face recognition system defines these landmarks as nodal points.Each human face has approximately 80 landmarks. Some of them are: • Distance between the eyes • Width of the nose • Shape of the cheek bones • Length of the jaw line
In past,face recognition system relied on comparing 2D images with another 2D images in data base. Person should be looking towards the camera. Even the slight variance in light or smile of a person creates the problem. This makes the system less effective.
Capturing the real time images of the person. Uses distinctive features of face. Can be used in darkness. Has the ability to recognize the person through different angles.
Detection:Acquiring an image by scanning or by using a video image. Aligment:Once the face is detected the system identifies the head’s position,size and pose.
Measurement: The system then measures the curves of the face on a sub-millimeter scale and creates a template. Representation: The system translates the template into a unique code.
Matching:The 3D image is matched with 3D image in the Database. Verification:In verification the image is verified with the one image in the database and result is displayed side wise.
Face recognition algorithms identify facial features by landmarks. Some of them are: • Principle Component Analysis(Eigenfaces) • Linear Discriminate Analysis. • Elastic Bunch Graph Matching. • Multilinear Subspace Learning(Tensor)
The Person in disguise cannot be caught. Less effective in huge crowd.
Technology is used by Law Enforcement Agencies. Can be used in Banking for identification. Can be used on airport for security purpose.
At present it is most promising for small or medium scale applications.such as office access and computer log in. It still face great technical challenges for large scale deployments.such as airport security. Advancement in hardware and software needed. Can emerge as Backbone of security system.