An Experimental Study Using Scale Invariant Feature Transform and Key-Point Extraction for Human Ear Recognition System

2019 ◽  
pp. 653-665
Author(s):  
Subhranil Som ◽  
Renuka Mahajan
Keyword(s):  
Experimental Study ◽  
Recognition System ◽  
Scale Invariant Feature Transform ◽  
Scale Invariant ◽  
Ear Recognition ◽  
Invariant Feature ◽  
Feature Transform ◽  
Human Ear ◽  
Scale Invariant Feature

scholarly journals Human – Ear Recognition Using Scale Invariant Feature Transform

2021 ◽  
pp. 1-12
Author(s):  
Abbas Hassin ◽  
Dheyaa Abbood
Keyword(s):  
Distance Measure ◽  
Recognition System ◽  
Scale Invariant Feature Transform ◽  
Morphological Operations ◽  
Scale Invariant ◽  
Ear Recognition ◽  
Invariant Feature ◽  
Feature Transform ◽  
Human Ear ◽  
Scale Invariant Feature

Biometrics techniques are the standard of a wide group of many applications for a human’s identification and verification issues. Because of this reason, a high scale of security needs to search for a new way to identify the person arises. In this paper, establish a human ear recognition system is proposed. This system combines four main phases: ear detection, ear feature extraction, ear recognition, and confirmation. The essential of the proposed system is to divide the ear image into the skin and non-skin pixels using a likelihood skin detector. The likelihood image processes by morphological operations to complete ear regions.  Scale-invariant feature transform uses for extracting the fixed features of the ear. Ear recognition includes two modes identification mode and verification mode. Euclidean Distance Measure (EDM) uses for similarity measure between the first image in the database and a new image. According to the three experiments conducted in this paper, the results of the different datasets, the accuracy ratio are 100%, 92%.and 92% respectively.

A Contactless Palm Vein Recognition System Based on Principle Line SIFT

2013 ◽  
Vol 347-350 ◽  
pp. 3469-3472 ◽  
Author(s):  
Wei Wu ◽  
Sen Lin ◽  
Hui Song
Keyword(s):  
Traditional Method ◽  
Recognition System ◽  
Scale Invariant ◽  
Limited Effect ◽  
Image Deformation ◽  
Invariant Feature ◽  
Feature Transform ◽  
Vein Recognition ◽  
Palm Vein ◽  
Scale Invariant Feature

Compared with the traditional method of contact collection, contactless acquisition is the mainstream and trend of palm vein recognition. However, this method may lead to image deformation caused by no parallel of the palm plane and the sensor plane. In order to improve the limited effect of Scale Invariant Feature Transform (SIFT) about this problem, a better method of palm vein recognition which based on principle line SIFT is proposed. Based on the self-built database, this method is compared with the SIFT and other typical palm vein recognition methods, the experimental results show that our system can achieve the best performance.

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