Texture classification using rotation-and scale-invariant gabor texture features

Riaz, Farhan, Hassan, Ali, Rehman, Saad and Qamar, Usman (2013) Texture classification using rotation-and scale-invariant gabor texture features. IEEE Signal Processing Letters, 20 (6). pp. 607-610. ISSN 1070-9908

Full content URL: https://doi.org/10.1109/LSP.2013.2259622

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Item Type:Article
Item Status:Live Archive


This letter introduces a novel approach to rotation and scale invariant texture classification. The proposed approach is based on Gabor filters that have the capability to collapse the filter responses according to the scale and orientation of the textures. These characteristics are exploited to first calculate the homogeneous texture of images followed by the rearrangement of features as a two-dimensional matrix (scale and orientation), where scaling and rotation of images correspond to shifting in this matrix. The shift invariance property of discrete fourier transform is used to propose rotation and scale invariant image features. The performance of the proposed feature set is evaluated on Brodatz texture album. Experimental results demonstrate the superiority of the proposed descriptor as compared to other methods considered in this letter.

Keywords:feature extraction, Discrete Fourier transforms, Vectors, Visualization, Training, Testing, Stability analysis
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:52398
Deposited On:18 Nov 2022 11:48

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