Title :
Texture classification based on statistical steganographic techniques
Author :
Ho, Yu-Kuen ; Wu, Mei-yi ; Jia-Hong Lee
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
Texture based features used for content based retrieval of images and videos should be invariant to various distortions such as noise corruption and compression. In this paper we apply statistical steganography techniques to extract robust texture features. Two texture classification methods, directional steganogaphy histogram (DSH) method and texture decision tree (TDT) method, are presented for texture analysis and classification. Experiments show that the proposed methods can achieve high accuracy rate and also work well even when the query textures are distorted by noise corruption or compression.
Keywords :
content-based retrieval; cryptography; data compression; feature extraction; image classification; image retrieval; image texture; accuracy rate; compression; content based retrieval; directional steganogaphy histogram; noise corruption; robust texture features; statistical steganographic techniques; texture classification; texture decision tree; Classification tree analysis; Content based retrieval; Decision trees; Feature extraction; Histograms; Image coding; Image retrieval; Noise robustness; Steganography; Videos;
Conference_Titel :
Circuits and Systems, 2002. APCCAS '02. 2002 Asia-Pacific Conference on
Print_ISBN :
0-7803-7690-0
DOI :
10.1109/APCCAS.2002.1115215