Influence of Confocal Scanning Laser Microscopy specific acquisition parameters on the detection and matching of Speeded-Up Robust Features

The robustness and distinctiveness of local features to various object or scene deformations and to modifications of the acquisition parameters play key roles in the design of many computer vision applications. In this paper we present the results of our experiments on the behavior of a recently developed technique for local feature detection and description, Speeded-Up Robust Features (SURF), regarding image modifications specific to Confocal Scanning Laser Microscopy (CSLM). We analyze the repeatability of detected SURF keypoints and the precision–recall of their matching under modifications of three important CSLM parameters: pinhole aperture, photomultiplier (PMT) gain and laser beam power. During any investigation by CSLM these three parameters have to be modified, individually or together, in order to optimize the contrast and the Signal Noise Ratio (SNR), being also inherently modified when changing the microscope objective. Our experiments show that an important amount of SURF features can be detected at the same physical locations in images collected at different values of the pinhole aperture, PMT gain and laser beam power, and further on can be successfully matched based on their descriptors. In the final part, we exemplify the potential of SURF in CSLM imaging by presenting a SURF-based computer vision application that deals with the mosaicing of images collected by this technique.

Research highlights
► Influence of pinhole aperture modifications on SURF detection and matching in CSLM images.
► Influence of photomultiplier gain modifications on SURF detection and matching in CSLM images.
► Influence of laser beam power modifications on SURF detection and matching in CSLM images.
► SURF-based automated mosaicing of CSLM images.