Multispectral imaging system for short wave infrared applications. - In: Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVIII, (2022), 120904Z, S. 120940Z-1-120940Z-14
A lot of applications as well as in the laboratory range and industrial range need a short-wave infrared imaging system. Especially multispectral imaging in that wavelength region are often enable new applications for quality assurance and monitoring of industrial processes. Due to the cost of the SWIR image sensors a multispectral imaging system should be flexible and adjustable to realize a maximum of applications. Normally push broom devices will fulfill these requirements. Disadvantages are that the sample must be moved, the spectral crosstalk and the blurring between the different channels can disturb the processing, and the correctness of spatial resolution along the scanning direction lead to uncertainties for dimensional measurements. For that reasons a twelve-channel filter-based imaging system was designed. A motor driven filter-wheel with a high precision drive will ensure that the filters will be placed in front of a SWIR Image sensor very precisely. To compensate the spectral aberrations along the optical axis a second drive positioning the image sensor into the focus plane. This enable sharp images in all spectral channels as well as high SNR (depends also on the capability of the SWIR Sensor). Furthermore, this implementation allows also to focus without changing the adjustment of the objective lens. A special designed dome light using halogen bulbs delivers very homogeneous radiation on the sample table. For the image readout, the control of the drives as well as the image presentation a software with a graphical user interface was developed. To export the image stacks in 3rd party software the imaging software saves the multispectral images in the envi-format.
https://doi.org/10.1117/12.2619350
Human-robot interaction booth with shape-from-silhouette-based real-time proximity sensor. - In: Dimensional Optical Metrology and Inspection for Practical Applications XI, (2022), 120980B, S. 120980B-1-120980B-9
Industrial robots have been an essential part of production facilities for many years. They allow fast and precise positioning of even the largest loads with very high repeatability. However, there are still many processes which are superiorly or more economically executed by humans. If a component requires several work steps, some of which are better suited to a robot and some to a human worker, cooperation between humans and robots would be beneficial. Due to the enormous power and speed of industrial robots, this poses a considerable risk to the worker. Therefore, tasks to be performed by humans and robots are usually completely decoupled in terms of space or time. We suggest an approach, which allows a human worker to interact safely with a fast industrial robot. We achieve this by constantly monitoring the position of both robot and human and adjusting the robot's velocity according to its proximity to the worker. We present an interaction booth, which can be entered by a robot arm from the back and a worker from the front such that they can both access the machinery within. A multicamera sensor, which is based on the shape-from-silhouette principle, constantly observes the booth to monitor its occupancy. We demonstrate that within 50 ms, our sensor can (1) detect a change in occupancy in the booth, (2) classify sub-volumes as "robot", "human", or "other object", (3) calculate the distance between human and robot, and (4) output this information to the robot controller. The working speed of the robot is then adjusted according to its distance to the worker.
https://doi.org/10.1117/12.2617069
Optimisation of a stereo image analysis by densify the disparity map based on a deep learning stereo matching framework. - In: Dimensional Optical Metrology and Inspection for Practical Applications XI, (2022), 120980D, S. 120980D-1-120980D-16
Stereo vision is used in many application areas, such as robot-assisted manufacturing processes. Recently, many different efficient stereo matching algorithms based on deep learning have been developed to solve the limitations of traditional correspondence point analysis, among others. The challenges include texture-poor objects or non-cooperative objects. One of these end-to-end learning algorithms is the Adaptive Aggregation Network (AANet/AANet+), which is divided into five steps: feature extraction, cost volume construction, cost aggregation, disparity computation and disparity refinement. By combining different components, it is easy to create an individual stereo matching model. Our goal is to develop efficient learning methods for robot-assisted manufacturing processes for cross-domain data streams. The aim is to improve recognition tasks and process optimisation. To achieve this, we have investigated the AANet+ in terms of usability and efficiency on our own test-dataset with different measurement setups (passive stereo system). Input of the AANet+ are rectified stereo pairs of the test-dataset and a pre-trained model. Instead of generating our own training dataset, we used two pre-trained models based on the KITTI-2015 and SceneFlow datasets. Our research has shown that the pretrained model based on the Scene Flow dataset predicts disparities with better object delimination. Due to the Out-of-Distribution inputs, only reliable disparity predictions of the AANet are possible for test data sets with parallel measurement setup. We compared the results with two traditional stereo matching algorithms (SemiGlobal block matching and DAISY). Compared to the traditionally computed disparity maps, the AANet+ is able to robustly detect texture-poor objects and optically non-cooperative objects.
https://doi.org/10.1117/12.2620685
Underwater 3D measurements with advanced camera modelling. - In: Journal of photogrammetry, remote sensing and geoinformation science, ISSN 2512-2819, Bd. 90 (2022), 1, S. 55-67
A novel concept of camera modelling for underwater 3D measurements based on stereo camera utilisation is introduced. The geometrical description of the ray course subject to refraction in underwater cameras is presented under assumption of conditions, which are typically satisfied or can be achieved approximately. Possibilities of simplification are shown, which allow an approximation of the ray course by classical pinhole modelling. It is shown how the expected measurement errors can be estimated, as well as its influence on the expected 3D measurement result. Final processing of the 3D measurement data according to the requirements regarding accuracy is performed using several kinds of refinement. For example, calibration parameters can be refined, or systematic errors can be decreased by subsequent compensation by suitable error correction functions. Experimental data of simulations and real measurements obtained by two different underwater 3D scanners are presented and discussed. If inverse image magnification is larger than about one hundred, remaining errors caused by refraction effects can be usually neglected and the classical pinhole model can be used for stereo camera-based underwater 3D measurement systems.
https://doi.org/10.1007/s41064-022-00195-y
Webbasierte integrierte Management- und Auditmanagementsysteme. - Ilmenau : Verlag ISLE, 2022. - IV, 216 Seiten
Technische Universität Ilmenau, Dissertation 2021
ISBN 978-3-948595-06-7
Durch steigende Ansprüche an Managementsysteme (zum Beispiel Qualität, Umwelt und Energie) aufgrund zunehmender Komplexität der Anforderungen von Normen und Richtlinien erhöht sich auch die Belastung der Unternehmen. Alle diese Anforderungen zu erfüllen und zu verwalten wird zunehmend schwieriger und aufwändiger. Da für viele Unternehmen nicht nur ein einzelnes, sondern mehrere Managementsysteme relevant sind, wird die Zusammenfassung dieser zu einem integrierten Managementsystem immer wichtiger. Dadurch können gleiche Anforderungen zusammengefasst und Synergieeffekte wahrgenommen werden. Integrierte Auditmanagementsysteme dienen zur Überprüfung dieser Anforderungen. In dieser Arbeit wird aufbauend auf den ermittelten Anforderungen ein neues webbasiertes integriertes Management- und Auditmanagementsystem konzeptioniert, entwickelt und getestet. Die hierzu durchgeführte Analyse verbreiteter softwarebasierter Managementsysteme zeigt, dass die Möglichkeiten der Integration verschiedener Managementsysteme nicht optimal genutzt werden. Aufgrund dessen, dass Synergieeffekte bisher nicht betrachtet wurden, sind wichtige Funktionen, welche den Verwaltungsaufwand reduzieren, nicht vorhanden. Um die Anforderungen aus der Praxis an webbasierte integrierte Management- und Auditmanagementsysteme zu ermitteln, wird zunächst eine empirische Untersuchung durchgeführt. Aufbauend auf den Studienergebnissen wird das theoretische Systemkonzept, welches neben webbasierten Technologien auch die Sicherheitsanforderungen und Datenorganisation berücksichtigt, entwickelt. Mit Hilfe eines solchen Systems kann die im Unternehmen vorhandene Datenorganisation (z. B. MS Office) mit aktuellen Softwarelösungen integriert werden, um den Implementierungsaufwand zu minimieren. Das System wird mit Hilfe des Client-Server-Modells implementiert, um die Zugänglichkeit zu gewährleisten. Insbesondere integrierte Auditmanagementsysteme reduzieren den Aufwand zur Vorbereitung, Durchführung und Nachbereitung eines Audits im Unternehmen. Durch Zuordnung der Anforderungen zu den relevanten Verantwortlichen und eine automatische Erstellung der Ergebnisse können genaue Maßnahmen festgelegt und verfolgt werden. Durch diese werden die Unternehmensprozesse kontinuierlich verbessert. Die Praxistauglichkeit des integrierten Management- und Auditmanagementsystems wurde unter realen betrieblichen Bedingungen in zwei mittelständischen Unternehmen getestet und validiert.
Multispectral imaging flow cytometry with spatially and spectrally resolving snapshot-mosaic cameras for the characterization and classification of bioparticles. - In: Micromachines, ISSN 2072-666X, Bd. 13 (2022), 2, 238, S. 1-12
https://doi.org/10.3390/mi13020238
Portable solution for high-resolution 3D and color texture on-site digitization of cultural heritage objects. - In: Journal of cultural heritage, ISSN 1296-2074, Bd. 53 (2022), S. 165-175
A peculiar characteristic of cultural heritage objects is their uniqueness. This results in an enormous importance for their preservation against aging, accidents, destruction etc. Although not replacing physical preservation, one way is the digitization of the objects in their current state by modern scanning technologies. This research describes a new method to combine 3D shape and color texture data acquired without contact to achieve high-resolution 3D representations. The method was basis of a portable 3D digitization system. The portable character allows its application on-site, which is essential for sensitive and non-transportable objects. A structured-light 3D sensor and a photo camera are used to capture the object from various overlapping perspectives. Then, the 3D shape and photographic data are processed and merged into a complete textured 3D model. Resolution and accuracy of the final model are in the range of 0.1 mm. Beyond preservation, the models can be used to make museum objects digitally available for experts or visitors worldwide e.g. in the form of online databases or virtual museums. A first utilization of the presented technology was realized with historic globes, especially with a Schöner globe dating from 1515 as highlight. The used method can be extended beyond RGB texture acquisition using multi-/hyperspectral sensors leading to an increased information content about the objects.
https://doi.org/10.1016/j.culher.2021.11.006
A high quality image stitching process for industrial image processing and quality assurance. - In: OCM 2021, (2021), S. 189-197
The size of the recording area of a camera is limited. The resolution of a camera image is also limited. To capture larger areas, a wide angle lens can be used, for example. However, the image resolution per unit area decreases. The decreased image resolution can be compensated by image sensors with a higher number of pixels. However, the use of a high pixel number of image sensors is limited to the current state of the art and availability of real image sensors. Furthermore the use of a wide angle lens has the disadvantage of a stronger distortion of the image scene. Also the viewing direction from a central location is usually problematic in the outer areas of a wide angle lens. Instead of using a wide angle lens, there is still the possibility to capture the large image scene with several images. This can be done either by moving the camera or by using several cameras that are positioned accordingly. In case of multiple image captures, the single use of the required image is a simple way to evaluat e a limited area of a large image scene with image processing. For example, it can be determined whether a feature limited by the size is present in the image scene. The use of this simple variant of a moving camera system or the use of single images makes it difficult or even impossible to use some image processing options. For example, determining the positions and dimensions of features that exceed a single image is difficult. With moving camera systems, the required mechanics add to the effort, which is subject to wear and tear and introduces a time factor. Image stitching techniques can reduce many of these problems in large image scenes. Here, single images are captured (by one or more cameras) and stitched together to fit. The original smaller single images are merged into a larger coherent image scene. Difficulties that arise here and are problematic for the use in industrial image processing are, among others: the exact positioning of the single images to each other and the actual joining of the imag es, if possible without creating disturbing artifacts. This publication is intended to make a contribution to this.
https://publikationen.bibliothek.kit.edu/1000128686
Improvement of thermal fringe projection for fast and accurate 3D shape measurement of transparent objects. - In: OCM 2021, (2021), S. 99-108
Structured light sensors for three-dimensional (3D) shape measurements working in the visible up to the shortwave infrared range have been intensively investigated in the last decades. Reliable measurements require diffuse reflection of the projected patterns. However, this condition is strongly limited or not fulfilled for transparent, translucent, shiny, or absorbing materials. Based on the scanning from heating approach, we have developed a two-step optical method for the measurement of such uncooperative objects. In this contribution, we present a simplified and robust projection technique of a focused single thermal fringe. Due to the irradiation of only locally strongly restricted areas, we obtain considerably higher intensities which enables us to reduce the total measurment time to or even below the second range while increasing the measurement accuracy. We show measurement results of non-opaque surfaces of objects made of a single material as well as of metal objects. Our customizable setup is of interest for quality assurance, bin picking, digitization, and many other areas of applications.
https://publikationen.bibliothek.kit.edu/1000128686
Multi-spectral imaging for Thermochromic Liquid Crystal based Particle Image Thermometry: a proof of concept. - In: International Symposium on Particle Image Velocimetry, ISSN 2769-7576, Bd. 1 (2021), 1, insges. 8 S.
In this contribution, a novel imaging approach for Thermochromic Liquid Crystal (TLC) based Particle Image Thermometry (PIT) is demonstrated. In contrast to state of the art approaches, a multi-spectral camera was used to record the color response of the Thermochromic Liquid Crystals seeding particles. An experiment with a transparent, water-filled, cylindrical cell as the central element was set up to investigate the novel approach. The temperature in the cell can be controlled by adjusting the temperature of the bottom and top plate. Calibration images at eleven different temperatures ranging from 18 ˚C to 21.6 ˚C, as well as images of a stable thermal stratification, were recorded. 90 percent of the calibration data was used to train a neural network (NN) to predict the temperature. The remaining 10 percent of the calibration data and the data of the stable thermal stratification were used to test the NN. The tests show that the deviation between predicted and ground truth temperature is mostly below 0.1 K and that the linear profile of the stable thermal stratification can be predicted with a maximum deviation of ≈ 0.15 K. This shows that multi-spectral imaging with neural networks for data processing is feasible and a promising concept.
https://doi.org/10.18409/ispiv.v1i1.168