A Pleliminary Study on Human Chewing Action Counter

This paper deals with a novel method which can estimate the occurrence number of human chewing actions by the help of image processing technique. At first, the user's mouth is recognized by the help of Haar cascade classifiers for human face and mouth. And then, this mouth image is processed with our proposed algorithm which can counter the occurrence number of human chewing action and can also reset the counter by confirming the mouth openness for new meal consumption. The experimental results show that it can be applied to improve chewing habits for kids.