Abstract:
Human face detection plays an important role in applications like face
recognition, video surveillance, human computer interface, face image database
management and many more. In modern multimedia systems, video and image
signals usually need to be indexed or retrieved according to their contents. In our
thesis, we implement a color characteristic for use in detection of frontal human
faces in color images with complex backgrounds i.e. a color based technique to
detect frontal human face had been developed and implemented. A technique for
detecting frontal human faces in color images is described that first separates
skin region from non-skin region and then locates faces within skin regions.
Using color information in an image is one of the various possible techniques for
face detection. The technique involves conversion of a color image into a gray
scale image in such a way that the gray values in the pixel shows the likelihood
of the pixel belonging to the skin. Obtained gray scale image is then segmented
to skin and non-skin regions, and a model face, representing front face is used in
template matching process to detect face within skin regions i.e. to find which of
the candidates is/are actually a face. Later, the false-positive and false-negative
errors of the implemented face detection technique on color images are
calculated. The experimental results show that this method can detect faces in
v
the images from different sources with good efficiency. Since faces are common
elements in video and image signals, the proposed face detection technique is
an advance towards the goal of content-based video and image indexing and retrieval.