Mosaicing of microscope images based on SURF

In this paper, we describe the design of a mosaicing technique for images from a microscope system with automatically controlled object stage and image capture unit. Due to the limited field of view in microscope imagery, larger objects are split up into many adjacent, but slightly overlapping frames. In many fields, such as medicine or biology, it is vastly beneficial that these image patches are recomposed to a single (panoramic) image. We propose a feature matching and registration method based on SURF (speeded-up robust features). This method is most accurate for microscopy images, which usually have repetitive, blob-like structures. Further steps in our algorithm are estimation of transformation parameters for image warping and blending for elimination of color and luminance differences between images. For feature matching, we propose a new method of dividing descriptor windows. This increases matching speed considerably. The experimental results provided demonstrate the performance of our method.