Predictive modeling toward identification of sex from lip prints - machine learning in cheiloscopy.

Cheiloscopy is a forensic investigation technique that deals with identification of humans based on lips traces. Lip traces hold multifarious features and could be analyzed in different ways to identify the links with personal identifying features. Machine Learning holds strong application in this domain, especially for pattern recognition and further interpretation. This work is focused on a brief survey of existing machine learning approaches in Cheiloscopy. Also, a comparative study of predictive models has been presented based on an original dataset of lip prints where supervised models have been used to predict the biological sex of the persons using their lip traces. Machine learning on one hand automatizes the identification process and poses a significant potential in analyzing huge number of lip traces with considerable accuracy.