Fuzzy object patterns for visual indexing and segmentation

Author

Lim, Joo-Hwee

Author_Institution

Inf.-Base Functions KRDL Lab, RWCP, Singapore, Singapore

Volume

1

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

77

Lastpage

80

Abstract

In this paper, we propose a fuzzy object pattern (FOP) for the representation of image content. The FOP is derived from view-based object recognition against a pre-defined vocabulary of visual object classes. Tessellation of FOPs over an image is further aggregated spatially to summarize the image content. This description scheme has been deployed in image indexing and retrieval on home photographs with very promising results. Furthermore, the FOP spans a new fuzzy pattern space in which incremental clustering is carried out to aggregate adjacent FOPs into larger regions. As a consequence, dominant regions can be segmented from an image

Keywords

content-based retrieval; database indexing; fuzzy set theory; image representation; image retrieval; image segmentation; object recognition; pattern clustering; photography; visual databases; vocabulary; adjacent pattern aggregation; description scheme; dominant regions; fuzzy object patterns; fuzzy pattern space; home photographs; image content represention; image content summarization; image indexing; image retrieval; image segmentation; incremental clustering; pattern tessellation; predefined vocabulary; spatial aggregation; view-based object recognition; visual indexing; visual object classes; Fuzzy sets; Histograms; Humans; Image segmentation; Indexing; Object detection; Object recognition; Prototypes; Shape measurement; Vocabulary;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2001. The 10th IEEE International Conference on

Conference_Location

Melbourne, Vic.

Print_ISBN

0-7803-7293-X

Type

conf

DOI

10.1109/FUZZ.2001.1007251

Filename

1007251