Depth and all-in-focus imaging by a multi-line-scan light-field camera

Štolc, Svorad; Soukup, Daniel; Holländer, Branislav; Huber-Mörk, Reinhold

doi:10.1117/1.jei.23.5.053020

Cited by 14 publications

(7 citation statements)

References 18 publications

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“…To maximize the robustness against occlusions, and to be able to inspect dark and glossy objects, we developed an inline Light Field (LF) acquisition setup and computational imaging algorithms, called Inline Computational Imaging (ICI) [29]: the algorithms combine depth information from the LF and the orientation of surface normals obtained by applying Photometric Stereo (PS)-algorithms to images from different illumination directions [30], [31]; applied calibration procedures and compensation for transport artifacts allow precise measurements [32], [33]. Additionally, it could be shown that the technology can be scaled to optical resolutions in the µm and sub-µm range [34].…”

Section: ) Multiview Stereo Systemsmentioning

confidence: 99%

Experimental Comparison of Optical Inline 3D Measurement and Inspection Systems

et al. 2021

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Fast optical 3D inline inspection sensors are a powerful tool to advance factory automation. Many of these visual inspection tasks require high speeds, high resolutions, and repeatability. Stereo vision, photometric stereo, light sectioning, and structured light are the most common principles for inline imaging in the several micrometers to sub-millimeter resolution range. Selecting the correct sensor principle can be challenging as manufacturers' datasheets frequently use different values to describe their systems and do not stick to proposed characterizations defined by the ''Initiative Fair Data Sheet'' or the VDE/VDI standards. With the help of standardized parameters, this paper aims to compare four different measurement principles, namely AIT's own single sensor light field camera method, a structured light pattern projector, a laser triangulation sensor, and a stereo camera system, with an approximate field of view of 100 × 100mm. We demonstrate simple yet meaningful experiments to determine lateral resolution, temporal noise, and calibration accuracy to enable an objective system comparison. Additionally, the reproduction of small surface structures and an overall performance on a challenging test object is evaluated. Results show that the measurement principles partly serve different application areas. The provided methods will help end users to select the correct sensor for specific applications.INDEX TERMS Automatic optical inspection, optical imaging, measurement accuracy, measurement precision, visual inspection, inline imaging, 3D imaging.

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Section: ) Multiview Stereo Systemsmentioning

confidence: 99%

Experimental Comparison of Optical Inline 3D Measurement and Inspection Systems

et al. 2021

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“…In state-of-the-art techniques, the surface normal component is either used directly or by converting it to gradient information, where the x - and y -component can be treated independently. Such an independent treatment can be beneficial for applications where data components are missing, as for example line-scanners [ 39 ].…”

Section: Depth and Surface Normal Cuesmentioning

confidence: 99%

A Review of Depth and Normal Fusion Algorithms

Antensteiner

Štolc

Pock

2018

Sensors

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Geometric surface information such as depth maps and surface normals can be acquired by various methods such as stereo light fields, shape from shading and photometric stereo techniques. We compare several algorithms which deal with the combination of depth with surface normal information in order to reconstruct a refined depth map. The reasons for performance differences are examined from the perspective of alternative formulations of surface normals for depth reconstruction. We review and analyze methods in a systematic way. Based on our findings, we introduce a new generalized fusion method, which is formulated as a least squares problem and outperforms previous methods in the depth error domain by introducing a novel normal weighting that performs closer to the geodesic distance measure. Furthermore, a novel method is introduced based on Total Generalized Variation (TGV) which further outperforms previous approaches in terms of the geodesic normal distance error and maintains comparable quality in the depth error domain.

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“…Crystals can move by as much as 15 mm s À1 owing to fluid dynamical effects (Savino & Monti, 1996) and will be further disturbed during mounting (Read & Meyer, 2000). Whilst most crystallography laboratories will have a stereoscopic microscope for manual mounting, stereoscopic digital imaging systems do not seem to offer a sufficient z-axis resolution at the necessary frame rate (Kwon et al, 2010;Pei et al, 2012;Dean et al, 2017;Š tolc et al, 2014;Levoy et al, 2006). Furthermore, the identification of protein crystals from digital images by software has proven to be exceptionally difficult because of significant variations between imaging conditions and crystal appearance; crystals are often very small ($10-75 mm), colourless, display poor optical contrast with the surrounding droplet (Nollert, 2003) and can be obscured by other droplet features.…”

Section: Introductionmentioning

confidence: 99%

The low-cost Shifter microscope stage transforms the speed and robustness of protein crystal harvesting

Wright¹,

Collins²,

Koekemoer³

et al. 2021

Acta Crystallogr D Struct Biol

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Despite the tremendous success of X-ray cryo-crystallography in recent decades, the transfer of crystals from the drops in which they are grown to diffractometer sample mounts remains a manual process in almost all laboratories. Here, the Shifter, a motorized, interactive microscope stage that transforms the entire crystal-mounting workflow from a rate-limiting manual activity to a controllable, high-throughput semi-automated process, is described. By combining the visual acuity and fine motor skills of humans with targeted hardware and software automation, it was possible to transform the speed and robustness of crystal mounting. Control software, triggered by the operator, manoeuvres crystallization plates beneath a clear protective cover, allowing the complete removal of film seals and thereby eliminating the tedium of repetitive seal cutting. The software, either upon request or working from an imported list, controls motors to position crystal drops under a hole in the cover for human mounting at a microscope. The software automatically captures experimental annotations for uploading to the user's data repository, removing the need for manual documentation. The Shifter facilitates mounting rates of 100–240 crystals per hour in a more controlled process than manual mounting, which greatly extends the lifetime of the drops and thus allows a dramatic increase in the number of crystals retrievable from any given drop without loss of X-ray diffraction quality. In 2015, the first in a series of three Shifter devices was deployed as part of the XChem fragment-screening facility at Diamond Light Source, where they have since facilitated the mounting of over 120 000 crystals. The Shifter was engineered to have a simple design, providing a device that could be readily commercialized and widely adopted owing to its low cost. The versatile hardware design allows use beyond fragment screening and protein crystallography.

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Depth and all-in-focus imaging by a multi-line-scan light-field camera

Cited by 14 publications

References 18 publications

Experimental Comparison of Optical Inline 3D Measurement and Inspection Systems

Experimental Comparison of Optical Inline 3D Measurement and Inspection Systems

A Review of Depth and Normal Fusion Algorithms

The low-cost Shifter microscope stage transforms the speed and robustness of protein crystal harvesting

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