Scene image analysis by using the sandglass-type neural network with a factor analysis

被引：0

作者：

Ito, S ^{[1
]}

Mitsukura, Y ^{[1
]}

Fukumi, M ^{[1
]}

Akamatsu, N ^{[1
]}

Omatu, S ^{[1
]}

机构：

[1] Univ Osaka Prefecture, Osaka, Japan

来源：

2003 IEEE INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN ROBOTICS AND AUTOMATION, VOLS I-III, PROCEEDINGS | 2003年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

It is difficult to obtain images only we want on the web. Because enormous data exist in the web. A present detection system of images are keyword detection which is added the name of keyword for images. Therefore, it is very important and difficult to add the keyword for images. In this paper, keywords in the image are analized by using the factor analysis and the sandglass-type neural network (SNN) for image searching. As images preprocessing, objective images are segmented by the maximin-distance algorithm. Small regions are integrated into a near region. Thus, objective images are segmented into some region. After this images preprocessing, keywords in images are analyzed by using factor analysis and a sandglass-type neural network (SNN) for image searching in this paper. Images data are compressed to a 2-dimensional space by using these two methods. This 2-dimensional data space is presented by a graph. Thus, keywords are analyzed in detail.

引用

页码：994 / 997

页数：4