Nonlinear Similarity Based Image Matching [chapter]

Muhammad Sirajul Islam, Les Kitchen
IFIP International Federation for Information Processing  
Image matching is an inarguably important operation for many practical sophisticated systems in machine vision and medical diagnosis. Many gray-level image matching applications use the sum-of-squared-difference (SSD) or sum-ofabsolute-differences (SAD), which are very sensitive to noise. Almost all images have some kind of noise, which causes the matching tasks significantly difficulty. In this paper we explore a new, less noise sensitive image-matching technique. It uses non linear similarity
more » ... n linear similarity measure min or median on interest points to find a match. The algorithm has been tested using a range of images with different gaussian noise. The result shows a significant improvement over traditional Euclidean distance measure technique for image matching.
doi:10.1007/978-0-387-44641-7_42 dblp:conf/ifip12/IslamK06 fatcat:p6ifp6az7jfn7evrkyeuawdonq