Bilinear equations and fuzzy image comparison

Is proposed a new image comparison index based on the greatest solution of a system of bilinear fuzzy relation equations A∙x=B∙x, where “∙” is the max-min composition, A and B are known images and x is an unknown vector. We show that this inde is more robust than the greatest and smallest eigen fuzzy set with respect to max-min composition a and on the Lukasiewicz t-norm with respect to the presence of noise introduced with several compression rates via fuzzy transforms

Bilinear equations and fuzzy image comparison

We present an image comparison method based on the greatest solution of a system of bilinear fuzzy relation equations A·x=B·x, where “·” is the max-min composition, A and B are the compared images, normalized in [0,1] and considered as fuzzy relations, and x is an unknown vector. Due to symmetry, A (resp. B) could be the original image and B (resp. A) is an image modified of A (resp. B) (for instance, either noised or watermarked). Our index is more robust than other two comparison indexes already known in literature