Multi-Threshold LIP Contour Detection

Abstract

In this work, we propose a novel, multi-threshold method for lip contour extraction from high-resolution static lip images acquired in an uncontrolled environment and emphasizing on the contour details. The introduced method is a “Divide and conquer” approach. We broke the problem of lip contour extraction into two base sub-problems of locating the upper and lower lip contours using a novel threshold selection algorithm and combining them into the solution for the original lip contour. The method was evaluated on a set of lip images taken from healthy subjects as well as on a set acquired from elder people with degraded lip shapes, and diagnosed with solar cheilosis. Our approach is a low complexity algorithm for robust and accurate lip contour extraction revealing shape details, which might be of value in diverse applied fields such as automated lip biometric and monitoring patients with affected lip contour.