Name
Abstract | ||
|---|---|---|
This study aims to segment objects within images of porcelain artifacts to help users retrieve the images in an efficient and convenient manner. Through digital archiving, a tremendous number of porcelain images have been created. To avoid interference due to the image's background during the retrieval process, it is necessary to segment objects in advance to accommodate high-precision image retrieval. In the proposed segmentation process, four texture features, including coarseness, contrast, directionality, and gradient, are first obtained. The morphological processing, which involves PCA (principal component analysis), Otsu's method, and object filter for opening and closing operation, is applied. Finally, regarding the objects selected by object filter, boundary extraction and watershed segmentation are performed to segment the porcelain objects from the background. In our image segmentation experiment using images of Chinese porcelain from various dynasties, featuring various shapes and colors, complete and accurate segmentation results are produced. The results can be used as a reference for future identification of the era to which the artifacts belong, and also to lay a foundation for future development of porcelain image retrieval techniques as a benefit to academic research. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.jvcir.2010.05.005 | J. Visual Communication and Image Representation |
Keywords | Field | DocType |
image segmentation experiment,accurate segmentation result,porcelain object,chinese porcelain,high-precision image retrieval,porcelain image retrieval technique,porcelain artifact,porcelain image,segment object,fast segmentation,object filter,texture feature,directionality,image retrieval,image segmentation,segmentation,watershed segmentation,contrast,principal component analysis,gradient | Computer vision,Scale-space segmentation,Pattern recognition,Segmentation,Image texture,Morphological processing,Image retrieval,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Mathematics,Principal component analysis | Journal |
Volume | Issue | ISSN |
21 | 7 | 1047-3203 |
Citations | PageRank | References |
2 | 0.38 | 18 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chuen-Horng Lin | 1 | 231 | 15.93 |
| Yu-Jhuang Syu | 2 | 2 | 0.72 |