Enhanced SEA algorithm and fingerprint classification

: This paper proposes the Enhanced Shrinking and Expanding Algorithm (ESEA) with a new categorization 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 categorization 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.

• Type: Journal
• Year: 2007
• Where: IJCAT
• Authors: Li-min Liu, Ching-Yu Huang, Tian-Shyr Dai, George Chang
• Keywords: Categorization Method, Fingerprint, Fingerprint Categorization Method, IJCAT 2007