Human face detection system by KenzanNET with preprocess analyzing hyperspectral image

Proposes a neural network system to detect human faces. Our scheme is composed of a preprocess and KenzanNET. Preprocessing analyzes hyperspectral images by using a hybrid self-organizing classification model to extract skin area and making a facial candidate pattern based on the extracted skin area. KenzanNET discriminates a face from other body parts. KenzanNET is a kind of feedforward neural network and is made from CombNET improved by an additional learning function. Under the various conditions in terms of background and brightness in a room and the distance between people and the camera, our system can detect human faces with 76.9% accuracy