Initial Displacement Estimation Method for Speckle Image Based on Marker Matching

Hongying, 张红颖 Zhang; Zhijing, 于之靖 Yu

doi:10.3788/aos201737.0303001

Cited by 2 publications

(1 citation statement)

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“…If seed point matching fails, subsequent matching becomes unfeasible. Hongying Zhang [12] assumed the deformation between left and right images was a homography transformation. They applied the improved Scale Invariant Feature Transform (SIFT) matching algorithm to estimate homography matrices through extracting the information from circular markers affixed to the object surface.…”

Section: Introductionmentioning

confidence: 99%

A digital speckle stereo matching algorithm based on epipolar line correction

Liu,

Niu,

et al. 2024

SIViP

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When the digital speckle correlation method takes images in some working conditions, the left and right images appear weak correlation due to the extreme inclination of the camera, which leads to the difficulty of matching. In order to solve the above problem, a digital speckle stereo matching algorithm based on epipolar correction is proposed in this paper, and an estimation method of deformational iterative initial values of the first-order shape function in the stereo matching process is given through theoretical derivation. The Newton-Raphson (NR) method can be directly used for fine matching in the original left and right images through the estimated deformational iterative initial value. The digital speckle matching experiment under different camera inclination angles of 24.2°, 34.2°, 41.15°, 47.3° and 52.4° is carried out to verify the effectiveness of the digital speckle stereo matching algorithm based on epipolar correction. The experimental results show that this method can complete the matching well under different inclined field of view, and the matching success rate is close to 100%, which can at least meet the requirement of digital speckle matching and deformation strain measurement under the inclination angle less than 52.4° field of view.

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Section: Introductionmentioning

confidence: 99%