Abstract
As next steps of Image Retrieval, it is very important to discriminate between “Typical Images” and “Peculiar Images” in the acceptable images, and moreover, to collect many different kinds of peculiar images exhaustively. As a solution to the 1st next step, my previous work has proposed a novel method to more precisely search the Web for peculiar images of a target object by its peculiar appearance descriptions (e.g., color-names) extracted from the Web and/or its peculiar image features (e.g., color-features) converted from them. This paper proposes a refined method equipped with cross-language (translation between Japanese and English) functions and validates its retrieval precision.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hattori, S., Tanaka, K.: Search the Web for typical images based on extracting color-names from the Web and converting them to color-features. Letters of DBSJ (Database Society of Japan) 6(4), 9–12 (2008)
Hattori, S., Tanaka, K.: Search the Web for peculiar images by converting Web-extracted peculiar color-Names into color-features. IPSJ (Information Processing Society of Japan) Transactions on Databases 3(1), 49–63 (2010)
Hattori, S.: Peculiar image search by Web-extracted appearance descriptions. In: Proceedings of the 2nd International Conference on Soft Computing and Pattern Recognition (SoCPaR 2010), pp. 127–132 (2010)
Hattori, S., Tezuka, T., Tanaka, K.: Extracting visual descriptions of geographic features from the Web as the linguistic alternatives to their images in digital documents. IPSJ Transactions on Databases 48(SIG11), 69–82 (2007)
Hattori, S., Tezuka, T., Tanaka, K.: Mining the Web for Appearance Description. In: Wagner, R., Revell, N., Pernul, G. (eds.) DEXA 2007. LNCS, vol. 4653, pp. 790–800. Springer, Heidelberg (2007)
Wikipedia - List of colors, http://en.wikipedia.org/wiki/List_of_colors
Japanese Industrial Standards Committee. Names of Non-Luminous Object Colours. JIS Z 8102:2001 (2001)
Smith, J.R., Chang, S.-F.: VisualSEEk: A fully automated content-based image query system. In: Proceedings of the 4th ACM International Conference on Multimedia (ACM Multimedia 1996), pp. 87–98 (1996)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hattori, S. (2012). Cross-Language Peculiar Image Search Using Translaion between Japanese and English. In: Gaol, F. (eds) Recent Progress in Data Engineering and Internet Technology. Lecture Notes in Electrical Engineering, vol 157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28798-5_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-28798-5_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28797-8
Online ISBN: 978-3-642-28798-5
eBook Packages: EngineeringEngineering (R0)