南南南南南南 南南南南南 Automatic Website Summarization by Image Content: A Case Study with Logo and Trademark Images Evdoxios Baratis, Euripides G.M. Petrakis, Member, IEEE, and Evangelos Milios, Senior Member, IEEE IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 20, NO. 9, SEPTEMBER 2008 Date : 2009/10/29 Speaker : Chin-Yen Yang
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南台科技大學 資訊工程系 Automatic Website Summarization by Image Content: A Case Study with Logo and Trademark Images Evdoxios Baratis, Euripides G.M. Petrakis, Member,
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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 20, NO. 9, SEPTEMBER 2008
Date : 2009/10/29
Speaker : Chin-Yen Yang
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Outline
INTRODUCTION1
IMAGE FEATURE EXTRACTION2
PROPOSED METHOD3
EXPERIMENTAL RESULTS4
5 CONCLUSIONS
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1. INTRODUCTION
We introduce the concept of image-based summarization
A fully automated image-based summarization approach is proposed
The evaluation of the method on corporate Websites is presented
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1. INTRODUCTION (C.)
Logos and trademarks are important characteristic signs of corporate Websites
A recent contribution reports that logos and trademarks comprise 32.6 percent of the total number of images on the Web
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2. IMAGE FEATURE EXTRACTION
Intensity histogram
Radial histogram
Angle histogram
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2. IMAGE FEATURE EXTRACTION (C.)
2.1 Image Representation
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3 PROPOSED METHOD
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3 PROPOSED METHOD (C.)
3.1 Image Information Extraction
1. Link information
2. Text Information
This information is displayed together with images or can be used for searching the Web
MaxDepth
LinkDepthMaxDepthDepth
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3 PROPOSED METHOD (C.)
3.2 Logo and Trademark Detection
Training the decision tree using histogram features outperforms training using raw histograms
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3 PROPOSED METHOD (C.)
Similarity detection
Three attributes corresponding to three histogram intersections, and one attribute corresponding to the euclidean distance of their vectors of moment invariants
The decision tree was pruned with a confidence value of 0.1 and achieved a 93.89 percent average classification accuracy
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3 PROPOSED METHOD (C.)
Image clustering
3.3 Duplicate Logo and Trademark Detection
From each cluster, one image is selected to represent the cluster in the summary