Abstract
The growing prevalence of multimedia systems is bringing the need for efficient techniques for storing and retrieving images into and from a database. In order to satisfy the information need of the users, it is of vital importance to effectively and efficiently adapt the retrieval process to each user. Considering this fact, an application for querying the images via their color, shape, and texture features in order to retrieve the similar salient objects is proposed. The features employed in content-based retrieval are most often simple low-level representations, while a human observer judges similarity between images based on high-level semantic properties. Using color, shape, and texture as an example, we show that a more accurate description of the underlying distribution of low-level features improves the retrieval quality. The performance experiments show that our application is effective in retrieval quality and has low processing cost.
This work is supported in part by Turkish State Planning Organization (DPT) under grant number 2004K120720, and European Commission 6th Framework Program MUSCLE Network of Excellence Project with grant number FP6-507752.
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Şaykol, E., Güdükbay, U., Ulusoy, Ö. (2004). Integrated Querying of Images by Color, Shape, and Texture Content of Salient Objects. In: Yakhno, T. (eds) Advances in Information Systems. ADVIS 2004. Lecture Notes in Computer Science, vol 3261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30198-1_37
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DOI: https://doi.org/10.1007/978-3-540-30198-1_37
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