A Novel Face Detection Algorithm for Occluded Images based on the Geometrical Model of Nose Point Extraction

Bikash Lamsal,Naofumi Matsumoto,Noriko Kojima

doi:10.12792/icisip2016.050

Abstract

Face detection is one of the developing trends in the field of biometrics. A lot of face detection algorithm has been developed, but still the face detection rate haven’t reached to 100%. It is due to the presence of various environmental conditions on an image. The occluded facial image is also one of the conditions for high performance face detection. A face is occluded if some area of the face is hidden behind on an object like a mask, sunglass, hand or we can say the face is visible partially. In this paper, we have developed a system that at first extracts the eyes, nose and mouth also known as the facial features by using the skin color model and the Haar cascades. The geometrical model is then applied to the extracted features using the three triangle method that calculates the height, width, distance and the position of the extracted features. Our proposed face detector then detects the presence of the face in an image even with an occlusion. The combination of the three triangle method with UKF and Haar cascade classifier represents the novelty of our proposed system. We performed our experiments on various images under different conditions, using different facial databases to clarify the effectiveness of our proposed method.

Highlights

The physiological biometric identifier that is widely used in person recognition is known as Face
We performed some experiments on different types of occluded images from CMU-MIT database, FDDB database and INRIA databases along with some images taken by ourselves under different occlusion conditions
The images that were not detected by our previous works due to the occlusion conditions are detected by using our current proposed method

Summary

Introduction

The physiological biometric identifier that is widely used in person recognition is known as Face. Human face detection is the first step of any face processing systems, computer vision and computational image analysis. The face detection has shown tremendous progress in this area, with emphasis on such application as biometric analysis, human machine interaction, robotics vision, image and video based coding and surveillance system. A lot of face detection algorithm has been developed, but the face detection hasn’t reached to the 100%. It is due to the presence of the different environmental conditions in an image. The environmental conditions for the face detection are image noise, illumination variant images, occlusion, pose, scale, expression etc. In our previous works we developed a face detection system(1),that works under the noisy images and the system(2) works on illuminant variant images. We were able to solve these conditions, but still some environmental conditions are left

Results

Discussion

Conclusion