AUTOMATIC PALMPRINT VERIFICATION

2001 ◽  
Vol 01 (01) ◽  
pp. 135-151 ◽  
Author(s):  
WEI SHU ◽  
GANG RONG ◽  
ZHAOQI BIAN ◽  
DAVID ZHANG
Keyword(s):  
Feature Extraction ◽  
Personal Identification ◽  
Classification Method ◽  
Projection Algorithm ◽  
Biometric Authentication ◽  
Determination Method ◽  
Matching Method ◽  
Line Feature ◽  
Remarkable Advantage

Automic palmprint verification is an important complement of biometric authentication. As the first attempt of personal identification by palmprint, this paper explores different methods for three main processing stages in palmprint verification including datum point registration, line feature extraction and palmprint classification. The datum points of palmprint which have the remarkable advantage of invariable location are defined and their determination method using the directional projection algorithm is improved. Then, line feature extraction and line matching method is described to detect whether a couple of palmprints are from the same palm. In addition, palmprint classification method based on the orientation property of the ridges is discussed to distinguish six typical cases. Various palmprint images have been tested to illustrate the effectiveness of the proposed methods.

scholarly journals Survey on finger-vein segmentation and authentication

2017 ◽  
Vol 7 (1.2) ◽  
pp. 9 ◽  
Author(s):  
Shwetambari Kharabe ◽  
C. Nalini
Keyword(s):  
Feature Extraction ◽  
Cost Efficiency ◽  
Personal Identification ◽  
Electronic Information ◽  
Basic Principles ◽  
Long Period ◽  
Finger Vein ◽  
Authentication Technique ◽  
Ideal Process ◽  
The Ideal

Exploding growth in the field of electronic information technology, the finger vein authentication technique plays a vibrant role for personal identification and verification. In recent era, this technique is gaining popularity, as it provides a high security and convenience approach for personal authentication. Vein biometrics is an emerging methodologycomparing to other systems, due to its strengths of low forgery risk, aliveness detection and stableness over long period of time. Literatures published based on different techniques used forand authentication process are described and evaluated in this paper. These processes hadgained an outstanding promise in variety of applications and much attention among researchers to provide combine accuracy, universality and cost efficiency. This paper in brief, reviews various approaches used for finger vein segmentation and feature extraction. The reviews are based on finger vein basic principles, image acquisition methodology, pre-processing functions, segmentation, feature extraction,classification, matching and identification procedures, which are analyzed scientifically, thoroughly and comprehensively.Based on the analysis, the ideal process and procedure is identified, which will be an idyllic solution for finger vein authentication.

Memory Efficient Vision Based Line Feature Extraction for Tiny Mobile Robots

2009 ◽  
pp. 287-296 ◽  
Author(s):  
Abdul Bais ◽  
Muhammad U. K. Khan ◽  
Khawaja M. Yahya ◽  
Robert Sablatnig ◽  
Ghulam M. Hassan
Keyword(s):  
Feature Extraction ◽  
Mobile Robots ◽  
Line Feature ◽  
Memory Efficient

Neural Networks on Handwritten Signature Verification

2011 ◽  
pp. 1232-1237
Author(s):  
J. Francisco Vargas ◽  
Miguel A. Ferrer
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Template Matching ◽  
Personal Identification ◽  
Signature Verification ◽  
Biometric Authentication ◽  
Cognitive Approach ◽  
Fractal Approach ◽  
Pattern Recognition Methods ◽  
Handwritten Signature

Biometric offers potential for automatic personal identification and verification, differently from other means for personal verification; biometric means are not based on the possession of anything (as cards) or the knowledge of some information (as passwords). There is considerable interest in biometric authentication based on automatic signature verification (ASV) systems because ASV has demonstrated to be superior to many other biometric authentication techniques e.g. finger prints or retinal patterns, which are reliable but much more intrusive and expensive. An ASV system is a system capable of efficiently addressing the task of make a decision whether a signature is genuine or forger. Numerous pattern recognition methods have been applied to signature verification. Among the methods that have been proposed for pattern recognition on ASV, two broad categories can be identified: memory-based and parameter-based methods as a neural network. The Major approaches to ASV systems are the template matching approach, spectrum approach, spectrum analysis approach, neural networks approach, cognitive approach and fractal approach. The proposed article reviews ASV techniques corresponding with approaches that have so far been proposed in the literature. An attempt is made to describe important techniques especially those involving ANNs and assess their performance based on published literature. The paper also discusses possible future areas for research using ASV.

An exemplar pyramid feature extraction based humerus fracture classification method

2020 ◽  
Vol 140 ◽  
pp. 109663
Author(s):  
Sukru Demir ◽  
Sefa Key ◽  
Turker Tuncer ◽  
Sengul Dogan
Keyword(s):  
Feature Extraction ◽  
Classification Method ◽  
Humerus Fracture ◽  
Fracture Classification
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