Approaches for Image Database Retrieval Based on Color, Texture, and Shape Features

Author:

Arora Kratika1,Aggarwal Ashwani Kumar1

Affiliation:

1. Sant Longowal Institute of Engineering and Technology, India

Abstract

With an ever-increasing use and demand for digital imagery in the areas of medicine, sciences, and engineering, image retrieval is an active research area in image processing and pattern recognition. Content-based image retrieval (CBIR) is a method of finding images from a huge image database according to persons' interests. Content-based here means that the search involves analysis of the actual content present in the image. As the database of images is growing day by day, researchers/scholars are searching for better techniques for retrieval of images with good efficiency.This chapter first gives an overview of the various image retrieval systems. Then, the applications of CBIR in various fields and existing CBIR systems are described. The various image content descriptors and extraction methods are also explained. The main motive of the chapter is to study and compare the features that are used in Content Based Image Retrieval system and conclude on the system that retrieves images from a huge database with good precision and recall.

Publisher

IGI Global

Reference28 articles.

1. Boissel, J. P., Cucherat, M., Amsallem, E., Nony, P., Fardeheb, M., Manzi, W., & Haugh, M. C. (2003). Getting evidence to prescribers and patients or how to make EBM a reality. Proceedings of the Medical Informatics Europe Conference (MIE ‘03), St. Malo, France.

2. Content-based image retrieval system based on combined and weighted multi-features

3. Histograms Analysis for Image Retrieval.;R.Brunelli;Pattern Recognition,2011

4. Texture analysis and classification with tree-structured wavelet transform

5. Chen, C.C. (2006). Using Tomorrow's Retrieval Technology to Explore the Heritage: Bonding Past and Future in the Case of Global Memory Net. Proceedings of theWorld Library and Information Congress, Seoul, Korea.

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