Image retrieval via the inhomogeneous diffusion of luminance and texture features

Andrea Kutics; Masaomi Nakajima; Taichi Nakamura; Hideyoshi Tominaga

doi:10.1117/1.482743

1 April 2000 Image retrieval via the inhomogeneous diffusion of luminance and texture features

Andrea Kutics, Masaomi Nakajima, Taichi Nakamura, Hideyoshi Tominaga

Journal of Electronic Imaging, Vol. 9, Issue 2, (April 2000). https://doi.org/10.1117/1.482743

A new method has been developed for measuring the similarity of two digital images using a common multiscale framework on luminance and texture features. This method applies a multivalued inhomogeneous diffusion model for luminance 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 is evaluated on the original and transformed images of Corel Gallery and Kodak photo-CD data by applying image scaling, rotation, and blurring. A similarity ratio of more than 95% is achieved for the first two transformations, and more than 80% for the third.

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Andrea Kutics, Masaomi Nakajima, Taichi Nakamura, and Hideyoshi Tominaga "Image retrieval via the inhomogeneous diffusion of luminance and texture features," Journal of Electronic Imaging 9(2), (1 April 2000). https://doi.org/10.1117/1.482743

Published: 1 April 2000

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