Open AccessLiterature Review on Fingerprint Level 1 and Level 2 Features Enhancement to Improve Quality of Image
Author(s) -
Krishna Prasad K,
P. S. Aithal
Publication year - 2017
Publication title -
international journal of management, technology, and social science
Language(s) - English
Resource type - Journals
ISSN - 2581-6012
DOI - 10.47992/ijmts.2581.6012.0020
Subject(s) - biometrics , fingerprint (computing) , computer science , artificial intelligence , feature (linguistics) , pattern recognition (psychology) , gait , computer vision , face (sociological concept) , orientation (vector space) , mathematics , physiology , social science , philosophy , linguistics , geometry , sociology , biology
Biometrics is the one most popular property in human distinguishing proof based on physical or behavioral features. The different physiological characteristics are Fingerprint, DNA, Face, hand, retina, ear features, and odor, where as behavioral characteristics or features are typing rhythm, gait, gesture, and voice with the basic premise that all are unique and all human beings are identified by these intrinsic traits. In the physiological traits, Fingerprint is most commonly utilized the biometric feature in diverse fields for identification and verification purpose. Fingerprint features can be separated into three noteworthy classifications in view of the granularity at which they are removed as level 1, level 2, and level 3 features. Level 1 feature contains macro details, which are easily extractable and include orientation filed, ridge frequency filed and pattern configuration. Only these global features or Level 1 features are not sufficient to uniquely identify or recognize, but if these features are used along with level 2 or level 3 features, that can make the fingerprint recognition system more robust and secure. Level1 features are used for image enhancement and orientation purpose. In this paper, we made a survey of existing literature on Level 1 features and try to analyze other researcher's contribution to this field.