Content Based Image Retrieval Using Texture and Color Extraction and Binary Tree Structure
Shubhangi C. Tirpude · 2011
Abstract— Content Based Image Retrieval is important research field in many applications. In this paper the CBIR system is implementing a new binary tree feature is used .Color and texture are commonly used in most of the CBIR system for finding similar images from the database to a given query image. In the implemented system color and texture are used as basic features to describe all the images. In addition, a binary tree structure is used to describe higher level features of an image. To extract color information, two histograms i.e. hue and saturation of the image are used. And to extract texture information image quantization and wavelet decomposition is applied to each image blocks. The Hue is quantized into 360 levels and the saturation into 100 levels. The binary tree structure is implemented based on some steps provided in (1).In this system, the feature extraction and wavelet decomposition for texture extraction is used to compute the feature vectors of image which helps in retrieval process. This approach combines the color and texture features and binary partitioning tree method in order to find the images similar to a specific query image. The Minkowski difference equation is used to measure the distance. The proposed system is implemented using the Matlab software.