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Image Mining: Techniques for Feature Extraction

Image Mining: Techniques for Feature Extraction

Tuğrul Taşci
Copyright: © 2016 |Pages: 30
ISBN13: 9781522500759|ISBN10: 1522500758|EISBN13: 9781522500766
DOI: 10.4018/978-1-5225-0075-9.ch004
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MLA

Taşci, Tuğrul. "Image Mining: Techniques for Feature Extraction." Intelligent Techniques for Data Analysis in Diverse Settings, edited by Numan Celebi, IGI Global, 2016, pp. 66-95. https://doi.org/10.4018/978-1-5225-0075-9.ch004

APA

Taşci, T. (2016). Image Mining: Techniques for Feature Extraction. In N. Celebi (Ed.), Intelligent Techniques for Data Analysis in Diverse Settings (pp. 66-95). IGI Global. https://doi.org/10.4018/978-1-5225-0075-9.ch004

Chicago

Taşci, Tuğrul. "Image Mining: Techniques for Feature Extraction." In Intelligent Techniques for Data Analysis in Diverse Settings, edited by Numan Celebi, 66-95. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-5225-0075-9.ch004

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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.

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