Andrea Kutics, Masaomi Nakajima, Taichi Nakamura, Hideyoshi Tominaga
Journal of Electronic Imaging, Vol. 9, Issue 02, (April 2000) https://doi.org/10.1117/1.482743
TOPICS: Image retrieval, Diffusion, Feature extraction, Image filtering, Image processing, Databases, RGB color model, Gaussian filters, Visualization, Systems modeling
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.