Combined Query Based Image Retrieval Using Structure Elements Descriptor


Gunho Lee, Minjoong Jeong, Journal of Information Processing Systems Vol. 21, No. 6, pp. 638-650, Dec. 2025  

https://doi.org/10.3745/JIPS.02.0232
Keywords: Global Descriptor, Image retrieval, Structural Element Descriptor
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Abstract

Similar image retrieval involves identifying and ranking images from a database based on visual attributes such as color, texture, and shape, with the goal of finding those most closely matching a given query image. This task requires precise analysis of image content to achieve accurate results. In this study, we propose an approach that incorporates structural information derived from an image segmentation model. This structural information highlights image characteristics, such as object shapes and their backgrounds, which are not fully captured by traditional dense global descriptors. By combining this structural information with global descriptors, our method captures both detailed shapes and broader image features in a user-controllable manner. Experimental results demonstrate the effectiveness of this integration approach in improving the performance of similarity search tasks.


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Cite this article
[APA Style]
Lee, G. & Jeong, M. (2025). Combined Query Based Image Retrieval Using Structure Elements Descriptor. Journal of Information Processing Systems, 21(6), 638-650. DOI: 10.3745/JIPS.02.0232.

[IEEE Style]
G. Lee and M. Jeong, "Combined Query Based Image Retrieval Using Structure Elements Descriptor," Journal of Information Processing Systems, vol. 21, no. 6, pp. 638-650, 2025. DOI: 10.3745/JIPS.02.0232.

[ACM Style]
Gunho Lee and Minjoong Jeong. 2025. Combined Query Based Image Retrieval Using Structure Elements Descriptor. Journal of Information Processing Systems, 21, 6, (2025), 638-650. DOI: 10.3745/JIPS.02.0232.