title: Study on clear stereo image pair acquisition method for small objects with big vertical size in SLM vision system.
abstract: Microscopic vision system with stereo light microscope (SLM) has been applied to surface profile measurement. If the vertical size of a small object exceeds the range of depth, its images will contain clear and fuzzy image regions. Hence, in order to obtain clear stereo images, we propose a microscopic sequence image fusion method which is suitable for SLM vision system. First, a solution to capture and align image sequence is designed, which outputs an aligning stereo images. Second, we decompose stereo image sequence by wavelet analysis theory, and obtain a series of high and low frequency coefficients with different resolutions. Then fused stereo images are output based on the high and low frequency coefficient fusion rules proposed in this article. The results show that Δw1 (Δw2 ) and ΔZ of stereo images in a sequence have linear relationship. Hence, a procedure for image alignment is necessary before image fusion. In contrast with other image fusion methods, our method can output clear fused stereo images with better performance, which is suitable for SLM vision system, and very helpful for avoiding image fuzzy caused by big vertical size of small objects.
authors.affiliation: College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China.
authors.forename: Yuezong
authors.initials: Y
authors.lastname: Wang
authors.affiliation: College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Jin
authors.affiliation: College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China.
authors.forename: Lika
authors.initials: L
authors.lastname: Wang
authors.affiliation: College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China.
authors.forename: Benliang
authors.initials: B
authors.lastname: Geng
keywords: image fusion; microscopic measurement; microscopic vision; stereo light microscope