Content-based color image retrieval Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/8c97kv51h

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  • 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.
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  • File scanned at 300 ppi (Monochrome, 8-bit Grayscale) using ScandAll PRO 1.8.1 on a Fi-6670 in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
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