Multiscale Blob Features for Gray Scale, Rotation and Spatial Scale Invariant Texture Classification

Author

Xu, Qi ; Chen, Yan Qiu

Author_Institution

Sch. of Inf. Sci. & Eng., Fudan Univ., Shanghai

Volume

4

fYear

0

fDate

0-0 0

Firstpage

29

Lastpage

32

Abstract

This paper proposes to apply a series of flexible threshold planes to the textured image and then use the topological and geometrical attributes of the blobs in the obtained binary images to describe image texture. The proposed multiscale blob features (MBF) is invariant to linear gray-level scaling and rotation, and is insensitive to uniform spatial scaling. The experiment results show that MBF offers very low error rate on the entire Brodatz texture database, and confirm its invariance properties

Keywords

geometry; image classification; image segmentation; image texture; Brodatz texture database; binary images; flexible threshold planes; geometrical blob attribute; image texture; linear gray-level scaling; multiscale blob features; spatial scale invariant texture classification; topological blob attribute; Humans; Image texture; Information processing; Information science; Laboratories; Object recognition; Robustness; Signal processing; Statistical analysis; Surface texture;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2006. ICPR 2006. 18th International Conference on

Conference_Location

Hong Kong

ISSN

1051-4651

Print_ISBN

0-7695-2521-0

Type

conf

DOI

10.1109/ICPR.2006.847

Filename

1699775