A method of image classification based on SIFT-Gabor-Scale descriptors

Author

Ming-Ming Huang ; Zhi-Chun Mu ; Hui Zeng

Author_Institution

Sch. of Autom. & Electr. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China

fYear

2014

fDate

13-16 July 2014

Firstpage

66

Lastpage

69

Abstract

In this paper, we propose a new method of image classification based on SIFT-Gabor-Scale descriptors. At first, we design the patch-based SIFT-Gabor-Scale descriptor by integrating SIFT and Gabor-Scale features. Then a compact image presentation is obtained with the sparse coding spatial pyramid matching (ScSPM) method. Finally, image classification is implemented effectively with the simple linear SVM. Experimental results show that the proposed approach has a better classification performance on Caltech-101 dataset comparing to other methods.

Keywords

image classification; image matching; transforms; Caltech-101 dataset; SIFT Gabor scale descriptors; ScSPM method; image classification method; image presentation; sparse coding spatial pyramid matching; Computer vision; Feature extraction; Gabor filters; Image classification; Image coding; Image representation; Pattern recognition; Gabor wavelet; Gabor-Scale; Image classification; SIFT; ScSPM;

fLanguage

English

Publisher

ieee

Conference_Titel

Wavelet Analysis and Pattern Recognition (ICWAPR), 2014 International Conference on

Conference_Location

Lanzhou

ISSN

2158-5695

Print_ISBN

978-1-4799-4212-1

Type

conf

DOI

10.1109/ICWAPR.2014.6961292

Filename

6961292