Search Space Reduction in Biometric Databases

Author:

Kavati Ilaiah1,Prasad Munaga V. N. K.2,Bhagvati Chakravarthy3

Affiliation:

1. IDRBT, India & UOH, India

2. IDRBT, India

3. University of Hyderabad, India

Abstract

Deployment of biometrics for personal recognition in various real time applications lead to large scale databases. Identification of an individual on such large biometric databases using a one-one matching (i.e., exhaustive search) increases the response time of the system. Reducing the search space during identification increases the search speed and reduces the response time of the system. This chapter presents a comprehensive review of the current developments of the search space reduction techniques in biometric databases. Search space reduction techniques for the fingerprint databases are categorized into classification and indexing approaches. For the palmprint, the current search space reduction techniques are classified as hierarchical matching, classification and indexing approaches. Likewise, the iris indexing approaches are classified as texture based and color based techniques.

Publisher

IGI Global

Reference102 articles.

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2. Abellanas, M., Bose, P., García-López, J., Hurtado, F., Nicolás, M., & Ramos, P. A. (2005, March). On properties of higher-order Delaunay graphs with applications. In EuroCG (pp. 119-122).

3. Indexing and retrieving in fingerprint databases under structural distortions

4. Score level fusion of voting strategy of geometric hashing and SURF for an efficient palmprint-based identification

5. Bay, H., Tuytelaars, T., & Van Gool, L. (2006). Surf: Speeded up robust features. In Computer vision–ECCV 2006 (pp. 404-417). Springer Berlin Heidelberg.

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