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Content-based image retrieval using ...

Wu, Mei.

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Content-based image retrieval using perceptual shape features.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Content-based image retrieval using perceptual shape features./
Author:	Wu, Mei.
Description:	51 p.
Notes:	Source: Masters Abstracts International, Volume: 43-06, page: 2296.
Contained By:	Masters Abstracts International43-06.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR00926
ISBN:	0494009268

Content-based image retrieval using perceptual shape features.
Wu, Mei.

Content-based image retrieval using perceptual shape features. - 51 p.

Source: Masters Abstracts International, Volume: 43-06, page: 2296.

Thesis (M.C.Sc.)--Dalhousie University (Canada), 2005.

A key issue in content-based image retrieval (CBIR) research is exploring how to bridge the gap between the high-level semantics of an image and its lower-level properties, such as color, texture and shape. In this thesis, we present a new method using a set of perceptual features, called generic edge tokens (GET), as image shape content descriptors for CBIR. GETS represent basic types of distinguishable edge segments including both linear and nonlinear features, which are modeled as qualitative shape descriptors based on perceptual organization principles. In the method, an image is first transformed into GET map on the fly. The basic GETS can be grouped into higher-level perceptual shape structures (PSS) as well as additional shape descriptors. Image content is represented statistically by a set of perceptual feature histograms (PFHs) of GETs and PSSs. Similarity is evaluated by comparing the differences between the corresponding PFHs from the two images. Experimental results are provided to demonstrate the potential of the proposed method.

ISBN: 0494009268Subjects--Topical Terms:

626642
Computer Science.

Content-based image retrieval using perceptual shape features.
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100 1 $a Wu, Mei. $3 1903064
245 1 0 $a Content-based image retrieval using perceptual shape features.
300 $a 51 p.
500 $a Source: Masters Abstracts International, Volume: 43-06, page: 2296.
502 $a Thesis (M.C.Sc.)--Dalhousie University (Canada), 2005.
520 $a A key issue in content-based image retrieval (CBIR) research is exploring how to bridge the gap between the high-level semantics of an image and its lower-level properties, such as color, texture and shape. In this thesis, we present a new method using a set of perceptual features, called generic edge tokens (GET), as image shape content descriptors for CBIR. GETS represent basic types of distinguishable edge segments including both linear and nonlinear features, which are modeled as qualitative shape descriptors based on perceptual organization principles. In the method, an image is first transformed into GET map on the fly. The basic GETS can be grouped into higher-level perceptual shape structures (PSS) as well as additional shape descriptors. Image content is represented statistically by a set of perceptual feature histograms (PFHs) of GETs and PSSs. Similarity is evaluated by comparing the differences between the corresponding PFHs from the two images. Experimental results are provided to demonstrate the potential of the proposed method.
590 $a School code: 0328.
650 4 $a Computer Science. $3 626642
690 $a 0984
710 2 0 $a Dalhousie University (Canada). $3 1017625
773 0 $t Masters Abstracts International $g 43-06.
790 $a 0328
791 $a M.C.Sc.
792 $a 2005
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR00926