Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1015508302797
Title: Image mining: Trends and developments
Authors: Hsu, W. 
Lee, M.L. 
Zhang, J. 
Keywords: Association rule mining
Image classification
Image clustering
Image indexing and retrieval
Image mining
Object recognition
Issue Date: 2002
Source: Hsu, W., Lee, M.L., Zhang, J. (2002). Image mining: Trends and developments. Journal of Intelligent Information Systems 19 (1) : 7-23. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1015508302797
Abstract: Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining.
Source Title: Journal of Intelligent Information Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/38967
ISSN: 09259902
DOI: 10.1023/A:1015508302797
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