A Novel SFP Extracting/Tracking Framework for Rigid Microstructure Measurement

3D measurement and reconstruction of rigid microstructures rely on the precise matches of structural feature points (SFPs) between microscopic images. However, most of the existing algorithms fail in extracting and tracking at microscale due to the poor quality of the microscopic images. This paper presents a novel framework for extracting and matching SFPs in microscopic images under two stereo microscopic imaging modes in our system, that is, fixed-positioning stereo and continuous-rotational stereo modes, respectively. A 4-DOF (degree of freedom) micro visual measurement system is developed for 3D projective structural measurement of rigid microstructures using the SFPs obtained from microscopic images by the proposed framework. Under the fixed-positioning stereo mode, a similarity-pictorial structure algorithm is designed to preserve the illumination invariance in SFPs matching, while a method based on particle filter with affine transformation is developed for accurate tracking of multiple SFPs in image sequence under the continuous-rotational stereo mode. The experimental results demonstrate that the problems of visual distortion, illumination variability, and irregular motion estimation in micro visual measurement process can be effectively resolved by the proposed framework.