A new indexing technique to retrieve images using integration of colour-size, texture and shape features

摘要

The purpose of this paper is to describe the designing of a content-based image retrieval (CBIR) system. Due to the enormous increase in image database sizes, as well as its vast deployment in various applications, the need for CBIR development arose. Firstly, this paper outlines a description of the primitive features like colour, texture and shape. Colour-size, novel feature is the combination of grey level histogram values and number of segments of the image. Texture features are extracted using LAWS texture features and shape features are retrieved using Zernike moments. After the extraction of primitive image features, the proposed kd-ORS tree is used for indexing the images in the database. The most relevant images are retrieved using the proposed kd-ORS tree. It is experimentally found that the proposed kd-ORS tree outperforms the other existing indexing methods.