PROJECT TITLE :

Incorporating skin color for improved face Detection and tracking system - 2016

ABSTRACT:

Face detection and tracking have wide applications, as an example, law enforcement, gaming, image search, marketing, etc. The detection and tracking tasks are quite challenging. Tracking the face in an image includes gender identification and segmenting the face using the skin color. In the past, many strategies have been proposed to spot a face in videos, like feature-based mostly detection, skin color segmentation, appearance, and eigen-based mostly identification. These techniques use image classifiers (both weak and strong) however don't seem to be terribly correct. This paper introduces a hybrid method that utilizes skin color for increasing accuracy of detection and tracking. In our technique, a picture is rescaled and divided primarily based on skin color, using RGB (red-inexperienced-blue) color combos. The divided skin tone image is combined with the edges of pictures before applying the morphological operations. As a final step, a bounding box seems on the detected face.