Overview¶
Description¶
Knomi Face Liveness provides software for performing liveness checking on facial images. This allows for detecting when a user presents a printed photo, video, or mask rather than a person.
Knomi Face Liveness provides this functionality in a robust solution with the following features:
Flexible Workflows - Knomi Face Liveness can be configured to support different capture scenarios and selection of security and usability tradeoff.
Ease of Integration - Knomi Face Liveness has a simple, easy to learn API using REST.
Support for Image Formats - Knomi Face Liveness supports importing images in a variety of formats. It supports images in BMP, TIF, PNG, and JPEG formats.
REST Design Goals¶
The REST design provides the following:
Performance between component interactions, which is important for user-perceived performance and network efficiency;
Scalability allowing to support large numbers of components and interactions among components;
Simplicity of a uniform interface;
Modifiability of components to meet changing needs;
Visibility of communication between components by service agents;
Portability of components by moving program code with the data;
Reliability in the resistance to failure at the system level;
Client–server architecture - The client–server provides the separation of concerns.
Statelessness - The client–server communication is constrained by no client context being stored on the server between requests. Each request from any client contains all the information necessary to service the request, and session state is held in the client.
Layered system - A client cannot ordinarily tell whether it is connected directly to the end server, or to an intermediary along the way. Intermediary servers can improve system scalability by enabling load balancing and by providing shared caches.
Uniform interface - The RESTful design decouples the different components of the system.
Security¶
Knomi Face Liveness supports TLS 1.2
Instructions on how to enable TLS can be found in section 3.1.