Abstract
This paper presents a new method for comparing the contents of two digital images using a common multiscale framework on color and texture features. The method applies a multi-valued inhomogeneous diffusion model on color and texture features to detect multiscale object boundaries. The orientations of the detected boundary points are utilized to obtain a similarity measure, which is defined by matching the orientation histogram pairs determined for each scale level. By applying normalization and histogram shifting, this measure can also address scale and rotation invariance. The method was evaluated on the original and transformed images of the Kodak CD album by applying image scaling, rotation and blurring. A similarity ratio of more than 95% was achieved for the first two transformations, and more than 80% for the third.
This work was supported by the Information-technology Promotion Agency, Japan(IPA).
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© 1998 Springer-Verlag London Limited
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Kutics, A., Nakamura, T., Nakajima, M., Tominaga, H. (1998). Image Matching via the Inhomogeneous Diffusion of Color and Texture Features. In: Marshall, S., Harvey, N.R., Shah, D. (eds) Noblesse Workshop on Non-Linear Model Based Image Analysis. Springer, London. https://doi.org/10.1007/978-1-4471-1597-7_35
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DOI: https://doi.org/10.1007/978-1-4471-1597-7_35
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