Design And Implementation of Face Detection and Recognition System
Face Detection and Recognition System – Face recognition system is an application for identifying someone from image or videos. Face recognition is classified into three stages ie)Face detection,Feature Extraction ,Face Recognition. Face detection method is a difficult task in image analysis. Face detection is an application for detecting object, analyzing the face, understanding the localization of the face and face recognition.It is used in many application for new communication interface, security etc.Face Detection is employed for detecting faces from image or from videos.
The main goal of face detection is to detect human faces from different images or videos.The face detection algorithm converts the input images from a camera to binary pattern and therefore the face location candidates using the AdaBoost Algorithm. The proposed system explains regarding the face detection based system on AdaBoost Algorithm . AdaBoost Algorithm selects the best set of Haar features and implement in cascade to decrease the detection time .The proposed System for face detection is intended by using Verilog and ModelSim,and also implemented in FPGA.
Face Detection System is to detect the face from image or videos. To detect the face from video or image is gigantic. In face recognition system the face detection is the primary stage. Figure 1 shows the various stages of face recognition system ie face detection, feature extraction and recognition. Now Face Detection is in vital progress in the real world
Face recognition is a pattern recognition technique and one of the most important biometrics; it is used in a broad spectrum of applications. The accuracy is not a major problem that specifies the performance of automatic face recognition system alone, the time factor is also considered a major factor in real time environments. Recent architecture of the computer system can be employed to solve the time problem, this architecture represented by multi-core CPUs and many-core GPUs that provide the possibility to perform various tasks by parallel processing. However, harnessing the current advancements in computer architecture is not without difficulties.
Motivated by such challenge, this research proposes a Face Detection and Recognition System (FDRS). In doing so, this research work provides the architectural design, detailed design, and four variant implementations of the FDRS.