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Neural networks for content based image retrieval

chapter
posted on 06.12.2017, 00:00 by Brijesh Verma, S Kulkarni
This chapter introduces neural networks for Content-Based Image Retrieval (CBIR) systems. It presents a critical literature review of both the traditional and neural network based techniques that are used in retrieving the images based on their content. It shows how neural networks and fuzzy logic can be used in interpretation of queries, feature extraction and classification of features by describing a detailed research methodology. It investigates a neural network based technique in conjunction with fuzzy logic to improve the overall performance of the CBIR systems. The results of the investigation on a benchmark database with a comparative analysis are presented in this chapter. The methodologies and results presented in this chapter will allow researchers to improve and compare their methods and it will also allow system developers to understand and implement the neural network and fuzzy logic based techniques for content based image retrieval.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Editor

Zhang Y

Parent Title

Semantic-based visual information retrieval

Start Page

p.

ISBN-10

159904370X

Publisher

IRM

Place of Publication

Hershey, USA

Open Access

No

External Author Affiliations

Faculty of Business and Informatics; University of Ballarat;

Era Eligible

Yes

Number of Chapters

16