JOURNAL ARTICLE

The Image Retrieval Based on Scale and Rotation-Invariant Texture Features of Gabor Wavelet Transform

Abstract

A scale and rotation invariant texture features extraction method is proposed and then the extracted texture features are used for image retrieval. In this method, firstly, features vector of each angle after the Gabor wavelet transform is multiplied by a Gaussian window, and then a circular shift is applied on it to shift the maximum value to be the first element, which makes the scale invariance achieved, then a circular shift is applied on the features vector to shift the maximum value to be the first element of each scale which makes the rotation invariant achieved. After that, texture features are extracted form the Gabor wavelet transform after scale and rotation invariant. Finally, the extracted texture features is used for images retrieval, the similarity is measured by Canberra distance and the retrieval effectiveness is assessed by P-R(Precision-Recall) carve and MAP(Mean Average Precision). The experimental results show that this method can accurately extract scale and rotation invariant texture features.

Keywords:
Artificial intelligence Pattern recognition (psychology) Wavelet transform Invariant (physics) Gabor wavelet Computer vision Gabor transform Mathematics Texture compression Scale invariance Image texture Texture filtering Rotation (mathematics) Computer science Wavelet Discrete wavelet transform Image processing Time–frequency analysis Image (mathematics) Statistics

Metrics

2
Cited By
0.00
FWCI (Field Weighted Citation Impact)
10
Refs
0.05
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Processing and 3D Reconstruction
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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