Fuzzy Similarity Measure and Fractional Image Query for Large Scale Protein 2D Gel Electrophoresis | Zendy

Daw-Tung Lin | Zendy; Juin-Lin Kuo | Zendy; En-Chung Lin | Zendy; SanYuan Huang | Zendy

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Fuzzy Similarity Measure and Fractional Image Query for Large Scale Protein 2D Gel Electrophoresis

Author(s) -

Daw-Tung Lin,

Juin-Lin Kuo,

En-Chung Lin,

SanYuan Huang

Publication year - 2005

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-28896-1

DOI - 10.1007/11553939_190

Subject(s) - matching (statistics) , computer science , similarity (geometry) , similarity measure , artificial intelligence , pattern recognition (psychology) , fuzzy logic , measure (data warehouse) , image (mathematics) , similitude , data mining , computer vision , mathematics , statistics

Spot matching is a challenging problem in two dimensional protein gel electrophoresis (2DGE) chromatography images analysis. It is necessary to provide a robust solution to the problem of querying and matching large scale for various size of 2DGE images. In this paper, we have developed a novel maximum relation spanning tree (MRST) algorithm which is capable of performing fast and accurate matching without the need for landmarks to be manually selected. In the matching process, we employ fuzzy similarity measuring technique to conclude the final decision of matching and location. The resultant system performs up to 94% correct matching for 225 2DGE test images. The additive value is the foundation of querying fractional gel images with large format gel images database.

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