Paper Info
Title
Temporal and longitudinal variances in wood log cross-section image analysis
Abstract
In this work two practical issues of biometric log recognition using log end images are investigated: Temporal and longitudinal variances of log cross-sections (CSs). These variances are related to the requirement of robustness for biometric characteristics. A texture feature-based fingerprint matching technique is used to compute matching scores between CS images. Our experimental evaluation is based on the temporal and longitudinal variances of 35 slices of a single tree log which where captured at four time delayed sessions. Results indicate, that biometric log recognition using log end images is robust and is able to overcome both issues. This work contributes to the development of a biometric log recognition system by showing that a texture feature-based matching technique is applicable to log CSs.
Year
DOI
Venue
2014
10.1109/ICIP.2014.7026154
Image Processing
Keywords
Field
DocType
biometrics (access control),image recognition,image texture,CS,biometric characteristics,biometric log recognition,log end images,longitudinal variances,temporal variances,texture feature based fingerprint matching technique,wood log cross section image analysis,Biometric log traceability,Cross-section analysis,Texture feature-based matching technique
Computer vision,Recognition system,Pattern recognition,Computer science,Robustness (computer science),Fingerprint,Artificial intelligence,Biometrics
Conference
ISSN
Citations 
PageRank 
1522-4880
3
0.57
References 
Authors
3
3
Name
Order
Citations
PageRank
Rudolf Schraml174.15
Johann Charwat-Pessler241.68
Andreas Uhl31958223.07