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Texture Image Retrieval: A Feature-Based Correspondence Method in Fourier Spectrum

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Abstract

This paper presents an effective texture descriptor invariant to translation, scaling, and rotation for texture-based image retrieval applications. The proposed texture descriptor is built taking the Fourier space of the image. In order to find the best texture descriptor, a quantization scheme based on Lloyd’s technique is proposed. As frequency descriptors are not invariant to all geometrical transformations as scaling and rotation, the modal analysis is applied to overcome these problems. Our image database is extracted from Brodatz album as well other sources. The proposed method is also compared with other content-based techniques and their performance is evaluated through several experiments. The effectiveness of both methods is measured by the commonly used retrieval performance measurement – Precision and Recall.

This work is partially supported by CAPES, FUNAPE and CNPq.

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Barcelos, C.A.Z., Ferreira, M.J.R., Rodrigues, M.L. (2005). Texture Image Retrieval: A Feature-Based Correspondence Method in Fourier Spectrum. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_48

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  • DOI: https://doi.org/10.1007/11552499_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28833-6

  • Online ISBN: 978-3-540-31999-3

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