Self-organizing Map (SOM) Based Data Navigation for Identifying Shape Similarities of Graphic Logos

In this paper, we propose a data navigation approach for identifying the shape similarity of graphic logo images using enhanced SOM based visualization methods. Existing SOM based visualization methods have the limitation of not being able to show detailed local distance information and global simil...

Full description

Saved in:
Bibliographic Details
Published in:Neural processing letters 2015-06, Vol.41 (3), p.325-339
Main Authors: Wang, Florence Y., Takatsuka, Masahiro
Format: Article
Language:English
Subjects:
Artificial Intelligence
Complex Systems
Computational Intelligence
Computer Science
Data compression
Datasets
Image enhancement
Logos
Navigation
Self organizing maps
Similarity
Visualization
Wavelet transforms
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we propose a data navigation approach for identifying the shape similarity of graphic logo images using enhanced SOM based visualization methods. Existing SOM based visualization methods have the limitation of not being able to show detailed local distance information and global similarity of data at the same time. Therefore, we propose two visualization approaches to overcome this limitation for better image data navigation. In our experiments, we used MPEG-7 shape image dataset and classic IRIS dataset to demonstrate our approaches are superior to previous approaches in providing sufficient local and global information for data visual navigation.
ISSN:1370-4621
1573-773X
DOI:10.1007/s11063-014-9375-4