Face Detection and Mood Recognition Music Player
Image processing is a growing field and one of its applications is Face recognition which is gaining attention of
many industries due to its wide range of applications. This Project explore the ways effectiveness of facial recognition can be
increased. This system is based on OpenCV and we also used Python to develop the project. The system uses
HAARCASCADE Face Database as reference for comparing. Face location is a developing innovation being utilized as a
part of an extensive variety of distinguishes human faces which are in computerized pictures. Face discovery additionally
implies a human ability to recognize diverse appearances. Face identification can be named as protest class recognition.
Protest class recognition, the errand is to discover the areas and sizes of all items in a computerized picture that have a place
with a particular class. Algorithms focus on frontal face of human for detection. If image matches with the image stores in
database, result is shown accordingly. Changing the database results in change of the results of previous inputs.