Bajrami, Buen and Kotevski, Zoran and Veljanovska, Kostandina (2023) Content Based Image Retrieval: Contemporary Trends and Challenges. In: International conference on Applied Internet and Information Technologies - AIIT2023, 13th October 2023, Bitola, North Macedonia.
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Abstract
Content Based Image Retrieval (CBIR) is a process that enables finding similar images in large sets of databases based on an image query. The purpose of CBIR engines is to mimic humans in the image classification process, thus a high computational cost is required to reach the proper selection of features which must be as unique as possible. Otherwise, the wrong choice of the model and then of the image features negatively affects the results by providing images that are not so similar to query image. In the last two decades, the number of researches related to CBIR has increased, but even today it is considered as difficult process. For this reason, the researchers in this field have developed various models and techniques that help in rendering the image, trying to make the results as accurate as possible. Some of these techniques include Local Binary Pattern (LBP) histogram, Local Difference Binary (LDB), Local Tetra Pattern (LTrP), etc. In this paper, we review the latest research in the field of CBIR, we compare their performance based on several factors, such as calculation time, image acquisition time, accuracy of results and we conclude the paper with a discussion about which models have shown the best performance and what are their advantages and disadvantages for which we make some recommendations for the future research.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Scientific Fields (Frascati) > Natural sciences > Computer and information sciences Scientific Fields (Frascati) > Engineering and Technology > Electrical engineering, electronic engineering,information engineering |
| Divisions: | Faculty of Information and Communication Technologies |
| Depositing User: | Prof. d-r. Zoran Kotevski |
| Date Deposited: | 08 Dec 2023 12:03 |
| Last Modified: | 08 Dec 2023 12:03 |
| URI: | https://eprints.uklo.edu.mk/id/eprint/9371 |
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