A Novel Method Of Wavelet Transform And Hilbert Curve In Content-based Image Retrieval

Modern techniques produce all kinds of information in different ways. Image is the most important multimedia information, and the amount of images is growing fast. Therefore, it becomes an urgent problem that how to find needed image efficiently in large-scale image database. The content-based image retrieval(CBIR) technique that search target images by low-level content feature is one of effective ways .In this paper, a novel image retrieval method base on wavelet transform and hilbert curve is proposed. The main contents and the technique route are following:1,The low frequency of the image is obtained using wavelet transform.2,The low frequency of the image is filled using Hilbert curve, Hilbert curve makes it become possible to retrieve a good character description by containing each pixel in the image for its specialty of the texture alignment and considering characters such as color, the distribution of the color, shape and so on.3,One dimension signal is Obtained by scanning Hilbert curve, secondly, carry out Discrete Cosine Transform(DCT) on the 1-D discrete signal, then use the first several DCT coefficients as feature vector of the image.4,Design and realize a simple retrieval system base on wavelet transform and Hilbert curve.The innovative point of paper: it is difficult to create Hilbert curve. To simple and convenient to create Hilbert curve,firstly, obtain the low frequency of the image by wavelet transform. then Hilbert curve fill the low frequency of the image. The experiments prove the image retrieval methods based on wavelet and Hilbert curve put forward in this thesis is effective and shortcut.