Abstract
Image pattern recognition in the field of big data has gained increasing importance and attention from researchers and practitioners in many domains of science and technology. This paper focuses on the usage of image pattern recognition for big data applications. In this context, the taxonomy of image pattern recognition and big data is revealed. The applications of image pattern recognition for big data, including multimedia, biometrics, and biology/biomedical, are also highlighted. Moreover, the significance of using pattern-based feature reduction in big data is discussed, and machine-learning techniques in pattern recognition applications are presented. A comparison based on the objectives of the approaches is presented to underline the taxonomy. This paper provides a novel review in exploring image recognition approaches for big data, which can be used in future research.
| Original language | English |
|---|---|
| Pages (from-to) | 10091–10121 |
| Number of pages | 30 |
| Journal | Multimedia Tools and Applications |
| DOIs | |
| Publication status | Published - 1 Apr 2018 |
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Zerdoumi, S., Sabri, A. Q. M., Kamsin, A., Hashem, I. A. T., Gani, A., Hakak, S., Al-garadi, M. A., & Chang, V. (2018). Image pattern recognition in big data: taxonomy and open challenges: survey. Multimedia Tools and Applications, 10091–10121. https://doi.org/10.1007/s11042-017-5045-7