Closed boundary face detection in grayscale images using watershed segmentation and DSFPN

In this paper we describe a face detection method from grayscale images using a watershed based region segmentation with a neural network classifier. The algorithm segments the image into regions using a watershed algorithm. The regions are later merged and filtered leaving highly probable face region candidates. Using the dynamic supervised forward propagation network (DSFPN), the system then verifies the possible candidate regions for faces and outputs the closed boundary for detected face regions.