Abstract
Search Engines such as Google is capable of processing user queries in a fast and efficient way. Though they are proven to be reliable, they are still incapable of handling complex queries. For example, Image Search Engines generally suffer from low accuracy when handling complex queries due to the lack of information available in an image. This paper presents the various image retrieval systems available currently, with in depth discussions on their operation and drawbacks. We also demonstrated the potential of using ontological technique in image retrieval systems, which has shown promising results in many research domains.
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Chan, C.S., Hong, J.L. (2013). A Comparative Study on Image Retrieval Systems. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42051-1_17
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