Ekstraksi Fitur Warna, Tekstur dan Bentuk untuk Clustered-Based Retrieval of Images (CLUE)
Abstract
Picture (image) is a media that used for storing visual data, for example, two-dimensional images are often used to store an incident. Images on the internet media growth very rapidly. There are a lot of image, video, text or other content on the Internet. Image Index and image retrieval again become a topic of research in the last decade in which concentrated on how to get the meaning of an information contained in an image. Three methods outlined in the search for an image, the text-based image retrieval, content-based image retrieval and indexing images in the order of language. This study focuses on the preparation of the features of an image based on color and texture. Features colors using the average value of Hue image, texture features using Gray Level occurance Matrix (GLCM). Color, texture, and shape extraction technique resulted in eighteen (18) feature that can be used as features in the process of Clustering.
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References
Parker, J.R. 2011. Algorithms for Image Processing and Computer Vision. Indianapolis: Wiley Publishing, Inc
Raghavan, Vijay. 1989. A Critical Investigation of Recaal and Precision as Measures of Retireval System Performance. ACM Transactions on Information Systems, Vol.7, Hal 205-229
J. Z. Wang, J. Li, and G. Wiedehold. 2001. SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture Libraries. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23 : 947-963
Ferguson, Jeremiah R. 2007. Using the Gray-Level Co-Occurrence Matrix to Segment and Classify Radar Imagery. Reno: University of Nevada
Madhulata, Soni. 2012. An Overview On Clustering Methods. IOSR Journal of Engineering, Vol2(4), Hal: 719-725
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