A novel approach to automatic detection of interest points in multiple facial images

Abstract

The human face includes different colors and forms due to its complexity. Therefore, facial image processing comprises even more problems than image processing of other objects. Interest point detection is one of the important problems in computer vision, which is the key aspect of solving problems such as facial expression analysis, age analysis, sex defining, facial recognition, and three-dimensional face modelling in augmented reality. To accomplish these tasks, facial interest points need automatic definition. A hybrid algorithm was developed to detect automatically interest regions and points in multiple images in the resented study. The study used processed facial images from an authorized image database with a resolution of 1600 x 1200, taken in standardized illumination conditions by using an InSpeck Mega Capturor II optical 3D structured light digitizer and 1000-W halogen lamp. The presented study integrated skin color analysis with the Haar classification method, processing 11 male and 25 female facial images with the developed algorithm. The average accuracy of facial interest point detection was 0.68 mm after testing all images.