In today’s revolution oriented environment, multimedia contents play a vital role in a wide range of applications, products and services. The high usage of these contents demand efficient searching and indexing for users. This demand has drawn substantial research attention towards image retrieval systems in the last few decades. Many great methods have been proposed, which offer numerous advantages like the following.
(i) These techniques are fully automatic and avoid the manual errors of text-based systems.
(ii) These techniques avoid complex tasks like annotation and also increase the accuracy of retrieval.
(iii) These techniques also reduce the amount of garbage, that is, irrelevant ...view middle of the document...
(i) Specify a visual query (example image)
(ii) Retrieve images similar to example image from the database
The present research work proposes Content Based Image Retrieval methodology based on the effective, synergistic integration of several schemes
(i) that perform preprocessing to improve the quality of retrieval
(ii) that efficiently extracts features that best describe the contents of both the query image and the database images
(iii) that improves the searching process to retrieve images from the database that are similar to the query image .
Advancements in hardware and software technology are motivating both users and researchers to search for techniques that challenge and improve the available industrial standards for retrieving images from huge archives. This can be performed either by developing new competitive methodologies or by enriching the operations of existing methodologies as several applications require reliable models, that are efficient both in the manner of finding similar images and reducing time complexity.
The solutions provided in this research work are more compatible for retrieving images from natural and photographic image databases and use an amalgamation of image processing and machine learning algorithms to perform retrieval in a fast manner while improving both the fraction of retrieved images that are relevant to the find and fraction of the images that are relevant to the query image that are successfully retrieved.
The methodology of the proposed research work is shown in Figure 3.1 and the...