NDLI: Robust partitioning and indexing for iris biometric database based on local features

Content Provider	IET Digital Library
Author	Khalaf, Emad Taha Mohammad, Muamer N. Moorthy, Kohbalan
Abstract	Explosive growth in the volume of stored biometric data has resulted in classification and indexing becoming important operations in image database systems. Consequently, researchers are focused on finding suitable features of images that can be used as indexes. Stored templates have to be classified and indexed based on these extracted features in a manner that enables access to and retrieval of those data by efficient search processes. This paper proposes a method that extracts the most relevant features of iris images to facilitate minimisation of the indexing time and the search area of the biometric database. The proposed method combines three transformation methods DCT, DWT and SVD to analyse iris images and extract their local features. Further, the scalable K-means++ algorithm is used for partitioning and classification processes, and an efficient parallel technique that divides the features groups causing the formation of two b-trees based on index keys is applied for search and retrieval. Moreover, search within a group is achieved using a proposed half search algorithm. Experimental results on three different publicly iris databases indicate that the proposed method results in a significant performance improvement in terms of bin miss rate and penetration rate compared with conventional methods.
Starting Page	589
Ending Page	597
Page Count	9
ISSN	20474938
Volume Number	7
e-ISSN	20474946
Issue Number	Issue 6, Nov (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/7/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2017.0130
Journal	IET Biometrics
Publisher Date	2018-04-24
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biomimetics Classification Processes Computer Vision And Image Processing Technique Discrete Cosine Transform Discrete Wavelet Transform Feature Extraction Half Search Algorithm Image Database System Image Fusion Image Matching Image Recognition Indexing Time Integral Transforms Iris Biometric Database Iris Biometric Image Iris Database Iris Recognition Local Feature Search Processes Singular Vector Decomposition Stored Biometric Data Stored Biometric TemPlate Visual Database
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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