• Title/Summary/Keyword: Web Image Features

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Web Image Clustering with Text Features and Measuring its Efficiency

  • Cho, Soo-Sun
    • Journal of Korea Multimedia Society
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    • v.10 no.6
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    • pp.699-706
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    • 2007
  • This article is an approach to improving the clustering of Web images by using high-level semantic features from text information relevant to Web images as well as low-level visual features of image itself. These high-level text features can be obtained from image URLs and file names, page titles, hyperlinks, and surrounding text. As a clustering algorithm, a self-organizing map (SOM) proposed by Kohonen is used. To evaluate the clustering efficiencies of SOMs, we propose a simple but effective measure indicating the accumulativeness of same class images and the perplexities of class distributions. Our approach is to advance the existing measures through defining and using new measures accumulativeness on the most superior clustering node and concentricity to evaluate clustering efficiencies of SOMs. The experimental results show that the high-level text features are more useful in SOM-based Web image clustering.

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The Effectiveness of High-level Text Features in SOM-based Web Image Clustering (SOM 기반 웹 이미지 분류에서 고수준 텍스트 특징들의 효과)

  • Cho Soo-Sun
    • The KIPS Transactions:PartB
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    • v.13B no.2 s.105
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    • pp.121-126
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    • 2006
  • In this paper, we propose an approach to increase the power of clustering Web images by using high-level semantic features from text information relevant to Web images as well as low-level visual features of image itself. These high-level text features can be obtained from image URLs and file names, page titles, hyperlinks, and surrounding text. As a clustering engine, self-organizing map (SOM) proposed by Kohonen is used. In the SOM-based clustering using high-level text features and low-level visual features, the 200 images from 10 categories are divided in some suitable clusters effectively. For the evaluation of clustering powers, we propose simple but novel measures indicating the degrees of scattering images from the same category, and degrees of accumulation of the same category images. From the experiment results, we find that the high-level text features are more useful in SOM-based Web image clustering.

Design and Implementation of the Content-Based Image Retrieval System using Color Features on the World Wide Web (WWW에서 칼라특징을 이용한 내용기반 화상검색 시스템의 설계 및 구현)

  • Choi, Hyun-Sub;Choi, Ki-Ho
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.9
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    • pp.2315-2332
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    • 1997
  • In this paper, we implement a content based image retrieval system for image searching by visual features from the image databases on WWW (world wide web). The image retrieval system finds the images that contain the most similar color regions after the system automatically extracts color features from the input image. We can select one of two query methods which use a full image of $4{\times}4$ 16 sketched color region. The image similarity is calculated on the histogram intersection distance and the histogram Euclidean distance. As the experimental results show that the two different query types provide the precision/recall 0.84/0.92 and 0.85/0.93 respectively, this retrieval system has been able to obtain high performance and validity.

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A Machine Learning Approach to Web Image Classification (기계학습 기반의 웹 이미지 분류)

  • Cho, Soo-Sun;Lee, Dong-Woo;Han, Dong-Won;Hwang, Chi-Jung
    • The KIPS Transactions:PartB
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    • v.9B no.6
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    • pp.759-764
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    • 2002
  • Although image occupies a large part of importance on the 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. In this paper classify the Web images from presently served Web sites to erasable or non-erasable classes. based on machine learning methods. For this research, we have detected 16 special and rich features for Web images and experimented by using the Baysian and decision tree methods. As the results, F-measures of 87.09%, 82.72% were achived for each method and particularly, from the experiments to compare the effects of feature groups, it has proved that the added features on this study are very useful for Web image classification.

Correlations between Users' Characteristics and Preferred Features of Web-Based OPAC Evaluation

  • Kim, Hee-Sop;Chung, Hyun-Soo;Hong, Gi-Chai;Moon, Byung-Ju;Park, Chee-Hang
    • ETRI Journal
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    • v.21 no.4
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    • pp.83-93
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    • 1999
  • This paper examines the correlations between user characteristics and their perferences for two selected features of Web-based OPAC systems. User characteristics identified in this study were age, gender, educational status, computer skills and OPAC experience. Usability features included interaction styles, character and image on screen, browsing and navigating style, screen layout, and ease of learning, whereas availability features attended to availability of information, quality of information and up-to-date information. Individual variables and features are described, and the correlation between the variables and the features are explored using Pearson's correlation coefficient(r). Although based on a small-scale sample survey, a considerably large number of statistically significant correlations were found between the users' characteristics and the selected evaluation features of interactive Web-based OPACs. From these observations, it seems to be suitable to recommend that system designers should make a more considered appraisal of the users' demographic characteristics in the design of the new generation of OPAC such as in user-tailored interactive Web-based OPAC systems.

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Managing and Modeling Strategy of Geo-features in Web-based 3D GIS

  • Kim, Kyong-Ho;Choe, Seung-Keol;Lee, Jong-Hun;Yang, Young-Kyu
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.75-79
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    • 1999
  • Geo-features play a key role in object-oriented or feature-based geo-processing system. So the strategy for how-to-model and how-to-manage the geo-features builds the main architecture of the entire system and also supports the efficiency and functionality of the system. Unlike the conventional 2D geo-processing system, geo-features in 3B GIS have lots to be considered to model regarding the efficient manipulation and analysis and visualization. When the system is running on the Web, it should also be considered that how to leverage the level of detail and the level of automation of modeling in addition to the support for client side data interoperability. We built a set of 3D geo-features, and each geo-feature contains a set of aspatial data and 3D geo-primitives. The 3D geo-primitives contain the fundamental modeling data such as the height of building and the burial depth of gas pipeline. We separated the additional modeling data on the geometry and appearance of the model from the fundamental modeling data to make the table in database more concise and to allow the users more freedom to represent the geo-object. To get the users to build and exchange their own data, we devised a file format called VGFF 2.0 which stands for Virtual GIS File Format. It is to describe the three dimensional geo-information in XML(eXtensible Markup Language). The DTD(Document Type Definition) of VGFF 2.0 is parsed using the DOM(Document Object Model). We also developed the authoring tools for. users can make their own 3D geo-features and model and save the data to VGFF 2.0 format. We are now expecting the VGFF 2.0 evolve to the 3D version of SVG(Scalable Vector Graphics) especially for 3D GIS on the Web.

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Managing Scheme for 3-dimensional Geo-features using XML

  • Kim, Kyong-Ho;Choe, Seung-Keol;Lee, Jong-Hun;Yang, Young-Kyu
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 1999.12a
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    • pp.47-51
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    • 1999
  • Geo-features play a key role in object-oriented or feature-based geo-processing system. So the strategy for how-to-model and how-to-manage the geo-features builds the main architecture of the entire system and also supports the efficiency and functionality of the system. Unlike the conventional 2D geo-processing system, geo-features in 3D GIS have lots to be considered to model regarding the efficient manipulation and analysis and visualization. When the system is running on the Web, it should also be considered that how to leverage the level of detail and the level of automation of modeling in addition to the support for client side data interoperability. We built a set of 3D geo-features, and each geo-feature contains a set of aspatial data and 3D geo-primitives. The 3D geo-primitives contain the fundamental modeling data such as the height of building and the burial depth of gas pipeline. We separated the additional modeling data on the geometry and appearance of the model from the fundamental modeling data to make the table in database more concise and to allow the users more freedom to represent the geo-object. To get the users to build and exchange their own data, we devised a fie format called VGFF 2.0 which stands for Virtual GIS File Format. It is to describe the three dimensional geo-information in XML(extensible Markup Language). The DTD(Document Type Definition) of VGFF 2.0 is parsed using the DOM(Document Object Model). We also developed the authoring tools for users can make their own 3D geo-features and model and save the data to VGFF 2.0 format. We are now expecting the VGFF 2.0 evolve to the 3D version of SVG(Scalable Vector Graphics) especially for 3D GIS on the Web.

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A Study on Features Analysis for Retrieving Image Containing Personal Information on the Web (인터넷상에서 개인식별정보가 포함된 영상 검색을 위한 특징정보 분석에 관한 연구)

  • Kim, Jong-Bae
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.3
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    • pp.91-101
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    • 2011
  • Internet is becoming increasingly popular due to the rapid development of information and communication technology. There has been a convenient social activities such as the mutual exchange of information, e-commerce, internet banking, etc. through cyberspace on a computer. However, by using the convenience of the internet, the personal IDs(identity card, driving license, passport, student ID, etc.) represented by the electronic media are exposed on the internet frequently. Therefore, this study propose a feature extraction method to analyze the characteristics of image files containing personal information and a image retrieval method to find the images using the extracted features. The proposed method selects the feature information from color, texture, and shape of the images, and the images as searched by similarity analysis between feature information. The result which it experiments from the image which it acquires from the web-based image DB and correct image retrieval rate is 89%, the computing time per frame is 0.17 seconds. The proposed method can be efficiently apply a system to search the image files containing personal information and to determine the criteria of exposure of personal information.

Binary Visual Word Generation Techniques for A Fast Image Search (고속 이미지 검색을 위한 2진 시각 단어 생성 기법)

  • Lee, Suwon
    • Journal of KIISE
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    • v.44 no.12
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    • pp.1313-1318
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    • 2017
  • Aggregating local features in a single vector is a fundamental problem in an image search. In this process, the image search process can be speeded up if binary features which are extracted almost two order of magnitude faster than gradient-based features are utilized. However, in order to utilize the binary features in an image search, it is necessary to study the techniques for clustering binary features to generate binary visual words. This investigation is necessary because traditional clustering techniques for gradient-based features are not compatible with binary features. To this end, this paper studies the techniques for clustering binary features for the purpose of generating binary visual words. Through experiments, we analyze the trade-off between the accuracy and computational efficiency of an image search using binary features, and we then compare the proposed techniques. This research is expected to be applied to mobile applications, real-time applications, and web scale applications that require a fast image search.

Stochastic Non-linear Hashing for Near-Duplicate Video Retrieval using Deep Feature applicable to Large-scale Datasets

  • Byun, Sung-Woo;Lee, Seok-Pil
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.8
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    • pp.4300-4314
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    • 2019
  • With the development of video-related applications, media content has increased dramatically through applications. There is a substantial amount of near-duplicate videos (NDVs) among Internet videos, thus NDVR is important for eliminating near-duplicates from web video searches. This paper proposes a novel NDVR system that supports large-scale retrieval and contributes to the efficient and accurate retrieval performance. For this, we extracted keyframes from each video at regular intervals and then extracted both commonly used features (LBP and HSV) and new image features from each keyframe. A recent study introduced a new image feature that can provide more robust information than existing features even if there are geometric changes to and complex editing of images. We convert a vector set that consists of the extracted features to binary code through a set of hash functions so that the similarity comparison can be more efficient as similar videos are more likely to map into the same buckets. Lastly, we calculate similarity to search for NDVs; we examine the effectiveness of the NDVR system and compare this against previous NDVR systems using the public video collections CC_WEB_VIDEO. The proposed NDVR system's performance is very promising compared to previous NDVR systems.