Proportional Analysis on Texture Image Retrieval Using Double Density 2D DWT and Double Density Dual Tree DWT

摘要

There has been a lot of research work dedicated towards texture image retrieval. However, with the wide spread of image usage in many fields of our lives, it becomes very important to develop new techniques for texture image retrieval. The large amount of image collections available from a variety of sources has posed increasing technical challenges to computer systems to store and index the image data. To make such collections easily accessible, here to search and retrieve the expected images from the database we need Content Based Image Retrieval system. The previous research in texture image retrieval was based on the famous techniques Gabor Wavelets and Discrete Wavelet Transform. In this paper, we introduce a texture image retrieval using Double Density 2D Discrete Wavelet Transform (DD 2D-DWT) and Double Density Dual Tree Discrete Wavelet Transform (DD DT-DWT) and comparative study of applying both Double Density 2D Discrete Wavelet Transform and Double Density Dual Tree Discrete Wavelet Transform techniques to the texture image retrieval. The main goal of this study is to exploit the advantages of using these techniques and to determine their performance on the basis of error rate and retrieval efficiency. Our experimental result shows the performance of Double Density 2D Discrete Wavelet Transform is much better than Double Density Dual Tree Discrete Wavelet Transform.