A new distance measure employing element-significance factors for robust image classification

Author

Kawahara, Kunio ; Shibata, Tadashi

Author_Institution

Dept. of Frontier Inf., Univ. of Tokyo, Kashiwa, Japan

fYear

2005

fDate

4-8 Sept. 2005

Firstpage

1

Lastpage

4

Abstract

A new simple distance measure has been proposed in which each vector element is weighted in the distance calculation according to its importance as determined by taking its statistics into account. In order to reflect the characteristics of the class, the element-significance factors are calculated based on intraclass variances and mean values of vector elements and utilized in the distance measure. The proposed distance measure has been applied to the face detection system and the cephalometric landmarks identification system which we developed in other work. Improved performances in image classification have been demonstrated.

Keywords

distance measurement; face recognition; image classification; vectors; cephalometric landmarks identification system; element-significance factors; face detection; intraclass variances; mean values; robust image classification; simple distance measure; vector elements; Face; Indexes; Silicon; Standards; Support vector machine classification; Vectors; Weight measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference, 2005 13th European

Conference_Location

Antalya

Print_ISBN

978-160-4238-21-1

Type

conf

Filename

7078355