Abstract
The studies related with the content-based image retrieval (CBIR) has increased because of both necessity for efficient image retrieval and the limitations in large-scale systems. Efficient image retrieval refers to finding accurate image from the database with high speed. This paper presents a new efficient image retrieval method using High Dimensional Model Representation (HDMR). The method has two main steps, clustering and retrieval. In clustering part, we use k-means method on HDMR constant term while in the subsequent part, we retrieve the most similar images to a given query image from a relevant cluster. We experiment the efficiency and effectiveness of the new algorithm on Columbia Object Image Library (COIL-100) and get conspicuous results. These results are tabulated in the paper.
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This work was supported by Research Fund of the Istanbul Technical University with project number 41411.
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Karcılı, A., Tunga, B. (2022). Content Based Image Retrieval Using HDMR Constant Term Based Clustering. In: Yilmaz, F., Queiruga-Dios, A., Santos Sánchez, M.J., Rasteiro, D., Gayoso Martínez, V., Martín Vaquero, J. (eds) Mathematical Methods for Engineering Applications. ICMASE 2021. Springer Proceedings in Mathematics & Statistics, vol 384. Springer, Cham. https://doi.org/10.1007/978-3-030-96401-6_3
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DOI: https://doi.org/10.1007/978-3-030-96401-6_3
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