Affiliation:
1. Sakarya University, Turkey
Abstract
In today's World, huge multi-media databases have become evident due to the fact that Internet usage has reached at a very-high level via various types of smart devices. Both willingness to come into prominence commercially and to increase the quality of services in leading areas such as education, health, security and transportation imply querying on those huge multi-media databases. It is clear that description-based querying is almost impossible on such a big unstructured data. Image mining has emerged to that end as a multi-disciplinary field of research which provides example-based querying on image databases. Image mining allows a wide variety of image retrieval and image matching applications intensely required for certain sectors including production, marketing, medicine and web publishing by combining the classical data mining techniques with the implementations of underlying fields such as computer vision, image processing, pattern recognition, machine learning and artificial intelligence.
Reference26 articles.
1. Airouche, M., Bentabet, L., & Zelmat, M. (2009, July). Image segmentation using active contour model and level set method applied to detect oil spills. In Proceedings of the World Congress on Engineering (Vol. 1, pp. 1-3).
2. A new multimodal fusion method based on association rules mining for image retrieval
3. Balan, S., & Devi, T. (2012). Design and Development of an Algorithm for Image Clustering In Textile Image Retrieval Using Color Descriptors. International Journal of Computer Science, Engineering and Applications, 2(3).
4. Image mining by content
5. Image mining framework and techniques: a review
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