Content-Based Image Retrieval Using Wavelet-based
Salient Points
Content-based Image Retrieval (CBIR) has become one of the most active research
areas in the past few years. Most of the attention from the research has been focused on indexing
techniques based on global feature distributions. However, these global distributions have limited
discriminating power because they are unable to capture local image information. Applying global Gabor
texture features greatly improve the retrieval accuracy. But they are computationally complex. In this
paper, we present a wavelet-based salient point extraction algorithm. We show that extracting the color
and texture information in the locations given by these points provides significantly improved results
in terms of retrieval accuracy, computational complexity and storage space of feature vectors as
compared to the global feature approaches.
Keywords: CBIR, Haarwavelet, wavelet-based salient points, Gabor filter
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