An analysis of content-based image retrieval

Year 2021, , 123 - 141, 15.04.2021

Hakan Koyuncu , Manish Dixit Baki Koyuncu

https://doi.org/10.35860/iarej.811927

Abstract

Nowadays, working on digital images is gaining much popularity in multimedia systems, due to the rapid increase in the utilization of large image databases. Thus, the Content-Based Image Retrieval (CBIR) method has become the most valuable method for these databases. This study mainly focuses on content-based image retrieval; which uses image features like color, shape, texture, etc. by searching the user query image from a large image database based on user request. CBIR is the most widely used technique as its searching capability is faster than the other traditional methods, and it works well in retrieving images automatically. It is also a big alternative approach to traditional methods. The CBIR techniques are used in many applications like surveillance detection, crime avoidance, fingerprint identification, E-library, medical, historical monument and biodiversity information systems, and many more. A total of 38 CBIR articles were comparatively analyzed.

Keywords

Content-Based Image Retrieval (CBIR), Feature Extraction, Performance measure, Shape, Texture, Tamura, Wavelet Transform

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