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Web image retrieval using majority-based ranking approach

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Abstract

Web image retrieval has characteristics different from typical content-based image retrieval; web images have associated textual cues. However, a web image retrieval system often yields undesirable results, because it uses limited text information such as surrounding text, URLs, and image filenames. In this paper, we propose a new approach to retrieval, which uses the image content of retrieved results without relying on assistance from the user. Our basic hypothesis is that more popular images have a higher probability of being the ones that the user wishes to retrieve. According to this hypothesis, we propose a retrieval approach that is based on a majority of the images under consideration. We define four methods for finding the visual features of majority of images; (1) majority-first method, (2) centroid-of-all method, (3) centroid-of-top K method, and (4) centroid-of-largest-cluster method. In addition, we implement a graph/picture classifier for improving the effectiveness of web image retrieval. We evaluate the retrieval effectiveness of both our methods and conventional ones by using precision and recall graphs. Experimental results show that the proposed methods are more effective than conventional keyword-based retrieval methods.

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Authors and Affiliations

  1. Multimedia Search Team, R&D Center, NHN Corp., 6th Floor Chorim Bldg., 6–3 Sunae-dong, Bundang-gu, Seongnam City, Gyeonggi-do, 463-825, Republic of Korea

    Gunhan Park

  2. Division of Computer Science and Engineering, Pusan National University, San-30, Jangjeon-dong, Keumjeong-gu, Busan, 609-735, Republic of Korea

    Yunju Baek

  3. Division of Computer Science, Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology, 373-1 Kusung-Dong, Yusong-Gu, Taejon, 305-701, Republic of Korea

    Heung-Kyu Lee

Authors
  1. Gunhan Park
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  2. Yunju Baek
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  3. Heung-Kyu Lee
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Correspondence to Gunhan Park.

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Park, G., Baek, Y. & Lee, HK. Web image retrieval using majority-based ranking approach. Multimed Tools Appl 31, 195–219 (2006). https://doi.org/10.1007/s11042-006-0039-x

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