Automated matching of pixel of interest between two digital images from two different microscope imaging devices

Matching is an essential operation towards automated registration of digital images. Registration of images is basically done either by studying the characteristics of the region surrounding the object of interest or by considering image morphological features. Many automated matching algorithms have been proposed and evaluated in the literature. However, previous studies on automated matching have either used a small number of benchmarks images in their evaluation, been directed at microscopy and not digital cameras, or have been based on ad hoc evaluation criteria. In this paper, we are presenting an image independent automated algorithm for pixel-to-pixel matching between two digital images obtained from two different microscope imaging devices. Here, SURF feature points and Euclidean distance measures are used for identifying key matching member index (KM
²
I). We have extensively tested our algorithm on a macro set of 1,69,000 digital images obtained from 250 pap smear samples. Experimental results prove that the proposed algorithm performs better for digital photography.