Abstract: The widespread of smart devices along with the exponential growth of virtual societies yield big digital image databases. These databases can be counter-productive if they are not coupled with efficient Content-Based Image Retrieval (CBIR) tools. The last decade has witnessed the introduction of promising CBIR systems and promoted applications in various fields. In this article, a survey on state of the art content based image retrieval including empirical and theoretical work is proposed. This work also includes publications that cover research aspects relevant to CBIR area. Namely, unsupervised and supervised learning and fusion techniques along with low-level image visual descriptors have been reported. Moreover, challenges and applications that emerged to support CBIR research have been discussed in this work.

Mohamed Maher Ben Ismail, “A Survey on Content-based Image Retrieval” International Journal of Advanced Computer Science and Applications(IJACSA), 8(5), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080521

@article{Ismail2017,
title = {A Survey on Content-based Image Retrieval},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080521},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080521},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {5},
author = {Mohamed Maher Ben Ismail}
}