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Image Retrieval by Shape Similarity
|關鍵字:||Content-Based Image Retrieval|
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In this thesis, we propose a new method for the design of a content-based image retrieval system based on shape. In our shape similarity retrieval, two shape features are extracted by using a new shape decomposition scheme. One is the proportion of the number of contour points in each quadrant, and the other is the number of contour points intersecting with the two level-1 quadrant-segmentation lines. With our proposed scheme, the shapes that have holes inside them can be handled. When a query shape is submitted to the system, the number of contour points intersecting with the two level-1 quadrant-segmentation lines is used along with a tolerance value to generate the lower bound and upper bound. Then, the shapes between these two bounds are compared to the query shape by using the proportion of the number of contour points in each quadrant. This will restrict the search space to a reasonable small proportion of the whole database. Finally, the shapes are displayed to user with increasing order based on their difference value. The experimental results show that our proposed scheme is efficient and accurate when search similar images.
|Appears in Collections:||資訊科學與工程學系所|
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