Image classification with structured self-organization map

Author

Wang, Z. ; Hagenbuchner, M. ; Tsoi, A.C. ; Cho, S.-Y. ; Chi, Z.

Author_Institution

Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Kowloon, China

Volume

2

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

1918

Lastpage

1923

Abstract

Adaptive processing of structured data using a supervised learning scheme has been successfully applied to many domains, e.g., molecular biology, image classification and retrieval. A self organizing map (SOM) type algorithm for processing of structured data using an unsupervised learning approach has previously been proposed. We present an approach using quadtree representation to extract an image structure, and the application of such a structured SOM to image classification problems. Encouraging results achieved by using only six simple visual features show that the structured SOM works well for structural information

Keywords

image classification; image representation; quadtrees; self-organising feature maps; adaptive processing; image classification; image content representation; quadtree representation; structured data; structured self-organization map; tree-structure image representation; Adaptive signal processing; Biomedical signal processing; Data engineering; Image classification; Image processing; Image representation; Image retrieval; Image segmentation; Supervised learning; Unsupervised learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on

Conference_Location

Honolulu, HI

ISSN

1098-7576

Print_ISBN

0-7803-7278-6

Type

conf

DOI

10.1109/IJCNN.2002.1007812

Filename

1007812