Research Of Content-Based Image Retrieval With Wavelet Analysis

CBIR (Content-Based Image Retrieval) which becoming more and more important technique in large image database organization and management is the combine of the image retrieval and traditional multimedia information retrieval. It approximately can be divided into many aspect, shape-based retrieval, color-based retrieval, texture-based retrieval, and so on.Wavelet analysis is the widely used time-frequency tool. The wavelet coefficient which produced by wavelet transform can best display part character of the image. This article has studied the wavelet analysis in the application of the CBIR. It concentrates the attention focal on using the wavelet analysis to get the texture and the shape characteristic.The texture is one kind of visual characteristic which reflect the homogeneity of picture and does not rely on the color or brightness phenomenon. The shape is one of essential characteristics, carries on the retrieval using the shape characteristic to be possible to enhance the retrieval the accuracy and the efficiency.This article uses the invariable tree-structure wavelet transformation to withdraw the picture texture characteristic to carry on the picture retrieval. This method can enhance the accurate rate of classification and reduces the data quantity in the very great degree and enhances the retrieval efficiency.To obtain the shape characteristic of the picture, we use the Wavelet Modulus Maximum method. Firstly, we should carries on the wavelet transformation to the picture to obtain the multi- criteria the mold picture. Next, I numerate the partial maximum value and the position of all the scales. Finally, using the multi- criteria unchanged moments as the characteristic retrieval images. This method can be an effective solution for image translation, scaling and rotating transform and so on.Through testing, we can see that these two methods for content-based image retrieval have very good results.