Ms. Soosun Cho Profile

Soosun Cho

at ETRI

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 10 January 2003 Paper

Image features for machine-learning-based approach for web image classification

Soosun Cho, Chi-Jung Hwang

Proceedings Volume 5018, (2003) https://doi.org/10.1117/12.479719

KEYWORDS: Image classification, Machine learning, Analytical research, Image analysis, Internet, Feature extraction, Statistical analysis, Databases, Infrared imaging, Astatine

Read Abstract +

The ubiquity of the Internet has brought about an increasing amount of multi-formatted Web documents. Although image occupies a large part of importance on these increasing Web documents, there have not been many researches for analyzing and understanding it. Many Web images are used for carrying important information but others are not used for it. If images in a Web document can be classified by which have particular information or not, then it would be very useful for analysis and multi-formatting of Web documents. In this paper we introduce the machine learning based methods of classifying Web images as either eliminable or non-eliminable. For this research, we have detected 16 special and rich features for Web images and experimented by using the Bayesian and decision tree methods. As the results, F-measures of 87.09%, 82.72% were achieved for each method and particularly, from the experiments to compare the effects of feature groups, it has proved that the selected features on this study are very useful for Web image classification.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years