Image Retrieval with Relational Semantic Indexing Color and Gray Images

Image Retrieval with Relational Semantic Indexing Color and Gray Images

Dr. S.Sutha

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Mr. C.A.Kandasamy

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Mr. N.Prakash

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Anna University, Chennai

Image Retrieval with Relational Semantic Indexing Color and Gray Images

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Abstract

Due to the development of digital technology large number of image is available in web and personal database and it take more time to classify and organize them. In AIA assigns label to image content with this image is automatically classified and desired image can be retrieved. Image retrieval is the one of the growing research area. To retrieve image Text and content based methods used. In recent research focus on annotation based retrieval. Image annotation represents assigning keywords to image based on its contents and it use machine learning techniques. Using image content with more relevant keywords leads fast indexing and retrieval of image from large collection of image database. Many techniques have been proposed for the last decades and it gives some improvement in retrieval performance. In this proposed work Relational Semantic Indexing (RSI) based LQT technique reduces the search time and increase the retrieval performance. This proposed method includes segmentation, feature extraction, classification, and RSI based annotation steps. This proposed method compared against IAIA, and LSH algorithms.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. S.Sutha. 2020. \u201cImage Retrieval with Relational Semantic Indexing Color and Gray Images\u201d. Global Journal of Computer Science and Technology - H: Information & Technology GJCST-H Volume 20 (GJCST Volume 20 Issue H1).

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GJCST Volume 20 Issue H1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-H Classification I.6.m

Submission ReceivedDecember 12, 2019
Peer Review Double Blind
Handling Editor
Accepted January 4, 2020
Published January 15, 2020

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v1.2

Issue date

October 16, 2020

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