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Content based Image Retrieval using Global Correlation Vector and Zernike Moments
Content Based Image Retrieval (CBIR) using color and shape features is discussed in this paper. Global Correlation Vector (GCV) is used for extracting color features and shape features are extracted by using Zernike Moments. The GCV is a combination of Color Histogram and Structure Element Correlation (SEC), by which it overcomes the problems that are encountered from either Color Histogram or SEC methods. Due to rotation invariance and fast computation Zernike Moments are suitable for image retrieval. The performance of our method is evaluated on Corel Gallery Magic database using the metrics such as Precision and Recall. The simulation results show that the performance of this method is superior to other existing methods.
Corel Gallery, Global Correlation Vector (GCV), HSV Color Space, Precision and Recall, Structure Element Correlation (SEC), Zernike Moments.
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