A new method of evaluation and optimization for feature extraction

Author

Jingyang, Gao ; Qunxiong, Zhu ; Chenglizhao, Chen

Author_Institution

Coll. of Inf. Sci. & Technol., Beijing Univ. of Chem. Technol., Beijing, China

fYear

2010

fDate

3-5 Dec. 2010

Firstpage

40

Lastpage

43

Abstract

The feature extraction and selection is one of the core issues of pattern recognition. In this paper, taking the feature extraction and selection for the letters A-Z and Arabic numbers 0-9 as object of study, the feature extraction methods are evaluated by calculating the sum, the variance and the minimum distance of Euclidean distance while the feature dimensions are 32, 64, 96 and 128. The arrangement of feature column element data is optimized according by their variances, the separability measure values of 1-128 dimensional features are calculated, and the Mix combination feature optimization method of feature selection for each dimension is proposed.

Keywords

feature extraction; natural language processing; optimisation; Arabic numbers; Euclidean distance; dimensional features; feature column element data; feature dimensions; feature extraction; feature selection; mix combination feature optimization method; pattern recognition; separability measure values; Computers; Euclidean distance; Face; Feature extraction; Optimization methods; Pattern recognition; evaluation and optimization; feature extraction; pattern recognition; the sum of Euclidean distance; the variance of Euclidean distance;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Application (ICCIA), 2010 International Conference on

Conference_Location

Tianjin

Print_ISBN

978-1-4244-8597-0

Type

conf

DOI

10.1109/ICCIA.2010.6141532

Filename

6141532