Abstract
Over a couple of years, huge attention is being paid by the researchers on the content-based image retrieval (CBIR) in order to successfully retrieve the contents from large-scale multimedia databases. Typically, each day gigabytes of multimedia contents are being generated by the digital camera, cell phone, and PC and they are available in the form of multimedia database. It is critical to find out the desired data from this vast collection of database. CBIR is not only efficient in performing the image retrieval, but also organizes the common contents of a digital library in the indented database. In this work, totally 25 research works are reviewed under CBIR techniques with respect to certain analytical views. On the basis of different algorithmic models, they are categorized into transform-based CBIR technique, metaheuristic-based CBIR technique, learning-based CBIR technique, fuzzy-learning-based CBIR technique, and other CBIR techniques. The analytical representations are defined by means of graphs and tabular columns. Finally, a detailed description of research gaps and challenges is also presented under this scenario.
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Bhatt, H.H., Mankodia, A.P. (2021). A Comprehensive Review on Content-Based Image Retrieval System: Features and Challenges. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_7
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