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Image Retrieval Based on Shape

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Modified on 2010/05/28 17:45 by Administrator Categorized as Digital Image Processing
Due to the tremendous increase of multimedia data in digital form, there is an urgent need for efficient and accurate location of multimedia information. For multimedia information to be located, it first needs to be effectively indexed or described to facilitate query or retrieval. At the moment, effective techniques exist for textual information indexing and retrieval. However, effective techniques for audio/visual information indexing and retrieval do not exist. Traditional index methods such as keyword indexing and textual annotation are not practical for audio/visual information indexing. This is because (i) they do not conform to a standard description language, (ii) they are inconsistent, (iii) they are subjective, i.e. they might not capture the content of the audio/visual information and (iv) they are time consuming. As the result, a new world standard MPEG-7, known as “Multimedia Content Description Interface”, has been developed to address the issue of audio/visual information description.



One of the most common multimedia data is image. Therefore, image description consists one of the key components of multimedia information description in MPEG-7. In MPEG-7, image is described by its contents featured by color, texture and shape. Many works have been done in image description, they are known as Content Based Image Retrieval (CBIR). Most researches on CBIR have contributed to color/texture based indexing and retrieval. Comparatively, little work has been done on image retrieval using shape.



Shape is one of key visual features used by human for distinguishing visual data along with other features of color and texture. Compare with color and texture, shape is easier for user to describe in the query, either by example or by sketch. While for color and texture feature, the query is usually presented by example, because it is impractical for ordinary users to sketch a colored or a textured image as query.

http://personal.gscit.monash.edu.au/~dengs/resource/papers/thesis_abstract.html

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