Real-Time Face Detection and Recognition in Complex Background

• DOI: 10.4236/jsip.2017.82007
• Publication Date: 2017-05-19T09:36:14Z
• Authors: Xin Zhang; Thomas Gonnot; Jafar Saniie
• Keywords: Haar-like features; Local Binary Patterns; Three-dimensional face recognition; Object-class detection; Cascading classifiers; Face hallucination; Feature (linguistics)

This paper provides efficient and robust algorithms for real-time face detection recognition in complex backgrounds. The are implemented using a series of signal processing methods including Ada Boost, cascade classifier, Local Binary Pattern (LBP), Haar-like feature, facial image pre-processing Principal Component Analysis (PCA). Boost algorithm is classifier to train the eye detectors with accuracy. LBP descriptor utilized extract features fast detection. reduces false rate. detected then processed correct orientation increase contrast, therefore, maintains high Finally, PCA used recognize faces efficiently. Large databases non-faces images validate algorithms. achieve an overall true-positive rate 98.8% 99.2% recognition.