Image Retrieval Systems: From Underlying Feature Extraction to High Level Intelligent Systems

Abstract

In this digital era, the profound amounts of complex images are being produced due to the up gradation of image capturing devices. So there is a huge demand of an efficient retrieval system for indexing and retrieving these images. Content based image retrieval (CBIR) system has been an active and promising research field in the area of image retrieval and processing. This system aims at retrieving the most appropriate and visually similar images from the large databases with the extraction of low level features of the images like color, edge and texture by various extraction techniques. This paper analyzes the basic CBIR system and the various achievements obtained in these systems mainly in the areas of feature extraction, indexing and intelligent CBIR systems. The most of the research in this area is now being focussed in developing of an advanced and intelligent CBIR system by using various deep learning algorithms which includes Convolutional neural network, auto encoders; long short term neural networks etc. so that the accuracy of the system can be improved. Finally, in the paper our insights and challenges are also provided for future research.