This project presents an interactive algorithm to automatically segment out a person’s face from a given image that consists of a head-and-shoulders view of the person and a complex background scene. The method involves a fast, reliable, and effective algorithm that exploits the spatial distribution characteristics of human skin color. The main objective of this research is to design a system that can find a person’s face from given image data. This problem is commonly referred to as face location, face extraction, or face segmentation. Regardless of the terminology, they all share the same objective. However, note that the problem usually deals with finding the position and contour of a person’s face since its location is unknown, but given the knowledge of its existence. If this is not known, then there is also a need to discriminate between “images containing faces” and “images not containing faces.” This is known as face detection. This work, however, focuses on face segmentation. The significance of this problem can be illustrated by its vast applications, as face segmentation holds an important key to future advances in human-to-human and human-to-machine communications. The segmentation of a facial region provides a content-based representation of the image where it can be used for encoding, manipulation, enhancement, indexing, modeling, pattern-recognition, and object-tracking purposes
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