Point matching techniques have been widely used in content-based image retrieval progress. In this paper, a new color image salient points detector is proposed based on wavelet transform and the Barnard Detector. First, an image is divided into three channels and each channel is decomposed with wavelet transform separately. Second, for a given wavelet coefficient, a corresponding wavelet coefficient could be found at a finer scale according to the absolute maximum value. Barnard Detector is used when finding potential salient points in the image. Finally, color salient points are extracted by using a self-adaptable threshold and the continuous points set reduction method. Experiments show that this method is robust and the extracted salient points can give a satisfying representation of an image. It can also improve the retrieval performance effectively.
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