Comparative Result On Feature Extractions Techniques For Human Ear Identification System Using Biometrics Ear Images

Abstract

Biometrics comprises the learning of automatic approaches for individual human beings based on physical or developmental characters. The difficulty of finding good biometric features and recognition systems has been studied broadly in current ages. This research reflects the use of ears as a biometric for human recognition. In this paper, feature extraction skills are applied such as Harris Feature, FAST Feature extraction and SURF Feature Extraction. All the images are taken from standard database and every image has different angles because of any criminal examination, accident, or ATM machine room camera taken different types of images. So, using different angular images feature extraction the research goes through these techniques to give the best result to the user.in this researcher used SIFT algorithm.

SIFT is an image local feature description process built on scale-space. Its strong similar capability, SIFT has numerous applications in different areas, such as image recovery, image edging, and machine idea. After SIFT was proposed, researchers have never stopped tuning it.