Abstract:
Identifying an individual with a picture has been popularized through the mass media and in
scientific research. However, it is less sturdy to fingerprint or membrane scanning. This report
describes the face detection and recognition mini-project undertaken for the seeing and
autonomy module at Creative IT Limited. It reports the technologies out there within the OpenComputer-Vision (OpenCV) library and methodology to implement them mistreatment
Python. For face detection, Haar-Cascades were used and for face recognition OpenCV,
Cascade classifiers and native binary pattern histograms were used. The methodology is
delineating together with flow charts for every stage of the system. Next, the results are shown
together with plots and screen-shots followed by a discussion of encountered challenges.