Content-based Retrieval of Kamon Images by Image Smoothing and Relaxation

Author(s)
Tachikawa, Takayuki
Kameyama, Keisuke
Kawabe, Tohru
Toraichi, Kazuo
Otsu, Nobuyuki
Kurita, Takio
Kwan, Paul Hing
Publication Date
2005
Abstract
A content-based retrieval method introducing smoothing is proposed. The main aim of this work is to construct a database of function approximated kamon images. By introducing smoothing, kamon images can be characterized. The proposed method can appropriately evaluate the 'similar' examples obtained by the questionnaire which is difficult to match by the conventional method.
Citation
Proceedings of the Eighth IASTED International Conference on Intelligent Systems and Control, p. 422-427
ISBN
0889865191
Link
https://hdl.handle.net/1959.11/4567
Language
en
Publisher
ACTA Press
Title
Content-based Retrieval of Kamon Images by Image Smoothing and Relaxation
Type of document
Conference Publication
Entity Type
Publication

Files:

NameSizeformatDescriptionLink