Abstract
Nowadays the computer systems created a various types of automated applications in personal identification like biometrics, face recognition techniques. Face verification has turn into an area of dynamic research and the applications are important in law enforcement because it can be done without involving the subject. Still, the influence of age estimation on face verification become a challenge to decide the similarity of pair images from individual faces considering very limited of data base availability. We focus on the development of image processing and face detection on face verification system by improving the quality of image quality. The main objective of the system is to compare the image with the reference images stored as templates in the database and to determine the age and gender.
Highlights
The importance of this paper is the design of image processing system and face recognition on face verification system to improve image quality with the purpose of identify the level similarity of face images based on the age stages and finding the gender of the persons
Brightness Preserving Dynamic Fuzzy Histogram Equalization (BPDFHE) method [3] is used for increasing brightness and contrast enhancement and translation of color images into grayscale to get accurate result
Histogram equalization is mainly useful in images with foregrounds and backgrounds that are both dark or both bright
Summary
The importance of this paper is the design of image processing system and face recognition on face verification system to improve image quality with the purpose of identify the level similarity of face images based on the age stages and finding the gender of the persons. The first step is Image processing where quality of face image is improved and enhanced using histogram equalization methods. The step is Feature extraction which is preprocessing level for age estimation and gender verification. Eigen faces are group of Eigen vectors mainly used in computer vision. This approach was developed by Sirovich and Kirby. We used eigenface mainly for age estimation.For Gender classification we used Fisherface algorithm. It uses Principal of Linear Discriminant Analysis method. Using this we find out whether the given image belongs to the gender female or male.
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