Title :
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
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;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.847