Work

New texture signatures and their use in rotation invariant texture classification

Year: 2002

Type: article

Abstract: -- In this paper, we present a theoretically and computationally simple but efficient approach for rotation invariant texture classification. This method is based on new texture signatures extracted from spectrum. Rotation invariant texture features are obtained based on the extension of the derived signatures. The features are tested with 1000 randomly rotated samples of 20 Brodatz texture classes. Comparative study results show that our method is highly efficient in rotation invariant texture classification. 1.

Authors: Jianguo Zhang, Tieniu Tan

Language: English

Topic: Image Retrieval and Classification Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1583433557

FWCI:

Cites: 13

Cited by: 8

Related to: 20