Software-Hardware Systems for Measurement of Sample Displacements in Probe Microscopes

Gulyaev, P. V.; Shelkovnikov, E. Yu.; Tyurikov, A. V.

doi:10.1007/s11018-019-01537-w

Cited by 1 publication

(1 citation statement)

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“…Thus, to increase the reliability of the determination of the scan overlap parameters, several methods for estimating these parameters should be used [45]: first, algorithmic methods for the image processing; and second, the values of the sensors mounted on the sample-positioning platform or displacement values obtained on the basis of the signals the sample-positioning platform drives. In our SPM we use the positioning platform where the leadscrews for manual control are equipped with inertia piezo-drives and sensors [45].…”

Section: Complexing Of the Methods Of Images Overlap Estimationmentioning

confidence: 99%

Particle and Particle Agglomerate Size Monitoring by Scanning Probe Microscope

et al. 2022

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In the present study, the use of a scanning probe microscope is described for monitoring the sizes of nanoparticles. Monitoring is the process of acquiring and analysing the set of overlapping images. The main analysis steps are image segmentation, determination of nanoparticles allocation and their sizes, determination of the overlap of images with one another, and exclusion of repeating measurements for the formation of the correct particle-size sampling. The thorough examination of commercial scanning probe microscopes, software, and image processing libraries showed that their capabilities are limited for image segmentation and determination of sizes in complex structured images. A method based on the surface curvature computation is proposed for the image segmentation (allocation of particles) and determination of particle sizes. The curvature is estimated using the surface area approximation with respect to the circumference. It is proposed to use sample displacement sensors as an aid for image stitching.

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Section: Complexing Of the Methods Of Images Overlap Estimationmentioning

confidence: 99%