Enhanced SEA algorithm and fingerprint classification. (21st February 2008)

• Record Type: Journal Article
• Authors: Liu, Li Min; Huang, Ching Yu; Dai, Tian Shyr; Chang, George
• Is Part Of: International journal of computer applications technology. Volume 30:Number 4(2007)
• Page Start: 295
• Page End: 302
• Publication Date: 2008-02-21
• Subjects: fingerprints -- fingerprint classification -- singular points -- SPs -- fault lines -- directional images -- shrinking and expanding algorithm -- SEA -- fingerprint analysis -- fingerprint identification -- biometrics; Technology -- Data processing -- Periodicals; 620.00285
• Languages: English
• ISSNs: 0952-8091

Abstract

This paper proposes the Enhanced Shrinking and Expanding Algorithm (ESEA) with a new categorisation method. The ESEA overcomes anomalies in the original Shrinking and Expanding Algorithm (SEA) which fails to locate Singular Points (SPs) in many cases. Experimental results show that the accuracy rate of the ESEA reaches 94.7%, a 32.5% increase from the SEA. In the proposed fingerprint categorisation method, each fingerprint will be assigned to a specific subclass. The search for a specific fingerprint can therefore be performed only on specific subclasses containing a small portion of a large fingerprint database, which will save enormous computational time.