A fully automated method for content-based color image retrieval is developed to extract color and shape content of an image. A color segmentation algorithm based on the k-mean clustering algorithm is used and a saturated distance is proposed to discriminate between two color points in the HSV color space. The feature set describing an image includes main object shape, which is extracted using the morphological operations. The computed image features are tagged within the image and a graphical user interface is presented for retrieving images based on the color and shape of the objects. The experimental results using natural color images demonstrate effectiveness of the proposed method. / Graduation date: 2000
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/33162 |
| Date | 24 September 1999 |
| Creators | Varanguien de Villepin, Audrey |
| Contributors | Kolodziej, Wojtek J. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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