39 research outputs found
Quality Assessment of Photographed 3D Printed Flat Surfaces Using Hough Transform and Histogram Equalization
Automatic visual quality assessment of objects created using additive manufacturing processes is one of the hot topics in the Industry 4.0 era. As the 3D printing becomes more and more popular, also for everyday home use, a reliable visual quality assessment of printed surfaces attracts a great interest. One of the most obvious reasons is the possibility of saving time and filament in the case of detected low printing quality, as well as correction of some smaller imperfections during the printing process. A novel method presented in the paper can be successfully applied for the assessment of at surfaces almost independently on the filament's colour. Is utilizes the assumption about the regularity of the layers visible on the printed high quality surfaces as straight lines, which can be extracted using Hough transform. However, for various colours of filaments some preprocessing operations should be conducted to allow a proper line detection for various samples. In the proposed method the additional brightness compensation has been used together with Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm. Results obtained for the database of 88 photos of 3D printed samples, together with their scans, are encouraging and allow a reliable quality assessment of 3D printed surfaces for various colours of filaments
Advanced surface color quality assessment in paper-based full-color 3d printing
Color 3D printing allows for 3D-printed parts to represent 3D objects more realistically, but its surface color quality evaluation lacks comprehensive objective verification considering printing materials. In this study, a unique test model was designed and printed using eco-friendly and vivid paper-based full-color 3D printing as an example. By measuring the chromaticity, roughness, glossiness, and whiteness properties of 3D-printed surfaces and by acquiring images of their main viewing surfaces, this work skillfully explores the correlation between the color representation of a paper-based 3D-printed coloring layer and its attached underneath blank layer. Quantitative analysis was performed using ÎE*ab, feature similarity index measure of color image (FSIMc), and improved color-image-difference (iCID) values. The experimental results show that a color difference on color-printed surfaces exhibits a high linear correlation trend with its FSIMc metric and iCID metric. The qualitative analysis of microscopic imaging and the quantitative analysis of the above three surface properties corroborate the prediction of the linear correlation between color difference and image-based metrics. This study can provide inspiration for the development of computational coloring materials for additive manufacturing
3D printing of oil paintings based on material jetting and its reduction of staircase effect
Material jetting is a high-precision and fast 3D printing technique for color 3D objects reproduction, but it also suffers from color accuracy and jagged issues. The UV inks jetting processes based on the polymer jetting principle have been studied from printing materials regarding the parameters in the default layer order, which is prone to staircase effects. In this work, utilizing the Mimaki UV inks jetting system with a variable layer thickness, a new framework to print a photogrammetry-based oil painting 3D model has been proposed with the tunable coloring layer sequence to improve the jagged challenge between adjacent layers. Based on contour tracking, a height-rendering image of the oil painting model is generated, which is further segmented and pasted to the corresponding slicing layers to control the overall printing sequence of coloring layers and white layers. The final results show that photogrammetric models of oil paintings can be printed vividly by UV-curable color polymers, and that the proposed reverse-sequence printing method can significantly improve the staircase effect based on visual assessment and color difference. Finally, the case of polymer-based oil painting 3D printing provides new insights for optimizing color 3D printing processes based on other substrates and print accuracy to improve the corresponding staircase effect
Experimental investigation of color reproduction quality of color 3D printing based on colored layer features
Color three-dimensional (3D) printing is an advanced 3D printing technique for reproducing colorful 3D objects, but it still has color accuracy issues. Plastic-based color 3D printing is a common color 3D printing process, and most factors affecting its color reproduction quality have been studied from printing materials to parameters in the fixed consecutive layers. In this work, and combined with variable stair thickness, the colored layer sequence in sliced layers of a specific 3D color test chart is deliberately changed to test the effects of colored layer features on its final color reproduction quality. Meanwhile, the colorimetric measurement and image acquisition of printed 3D color test charts are both achieved under standard conditions. Results clearly show that the chromatic aberration values and mean structural similarity (MSSIM) values of color samples have a significant correlation with the colored stair thickness, but both did not display a linear relationship. The correlation trends between colored layer sequence and the above two indexes are more localized to the colored stair thickness. Combined with color structural similarity (SSIM) maps analysis, a comprehensive discussion between colored layer features and color reproduction quality of color 3D printing is presented, providing key insights for developing further accurate numerical models
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Intelligent laser scanning for computer aided manufacture.
Reverse engineering requires the acquisition of large amounts of data describing the surface of an object, sufficient to replicate that object accurately using appropriate fabrication techniques. This is important within a wide range of commercial and scientific fields where CAD models may be unavailable for parts that must be duplicated or modified, or where a physical model is used as a prototype. The three-dimensional digitisation of objects is an essential first step in reverse engineering. Optical triangulation laser sensors are one of the most popular and common non-contact methods used in the data acquisition process today. They provide the means for high resolution scanning of complex objects. Multiple scans of the object are usually required to capture the full 3D profile of the object. A number of factors, including scan resolution, system optics and the precision of the mechanical parts comprising the system may affect the accuracy of the process. A single perspective optical triangulation sensor provides an inexpensive method for the acquisition of 3D range image data
Computer-aided diagnosis in chest radiography
Chest radiographs account for more than half of all radiological examinations; the chest is the mirror of health
and disease. This thesis is about techniques for computer analysis of chest radiographs. It describes methods for
texture analysis and segmenting the lung fields and rib cage in a chest film. It includes a description of an
automatic system for detecting regions with abnormal texture, that is applied to a database of images from a
tuberculosis screening program
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Improving precision of material extrusion 3D printing by in-situ monitoring and predicting 3D geometric deviation using Conditional Adversarial Networks
The field of additive manufacturing, especially 3D printing, has gained growing attention in the research and commercial sectors in recent years. Notwithstanding that the capabilities of 3D printing have moved on to enhanced resolution, higher deposition rate, and a wide variety of materials, the crucial challenge of verifying that the component manufactured is within the dimensional tolerance as designed continues to exist. Material extrusion 3D printing has long been established for rapid prototyping and functional testing in many research and industry fields. However, its inconsistency and intrinsic defects (surface roughness and geometric inaccuracies) hinder its application in several areas, most notably âcertify-as-you- buildâ small-batch prototyping and large-batch production.In this study, we present an approach to reduce both inconsistency and the 3D geometric inaccuracies of products fabricated by material extrusion.1. This work developed and demonstrated an approach for layer-by-layer mapping of 3D printed parts, which can be used for validation of printed models and in situ adjustment of print parameters. This in situ metrology system scans each layer at the time of printing, providing a 3D model of the as-printed part. A high-speed optical scanning system was integrated with a Material Extrusion type 3D printer to achieve in situ monitoring of dimensional inaccuracies during printing, which leaves the door open to implement a closed-loop feedback system to compensate geometric errors during printing in the future and fabricate âcertify-as-you-buildâ products.2. This work trained machine learning algorithms with data from this scanning system and predicted 3D geometric inaccuracies in new designs. Eight Conditional Adversarial Networks (CAN) machine learning models were trained on a limited number of scanned profile images of different layers, consisting of less than 50 actual images and 50 generated images, to predict the 3D geometric deviations of freeform shapes. The generated images were produced by randomly combining and cropping the actual images without any distortion. These CAN models produced predictions where at least 44.4%, 87.6%, 99.2% of data were within ïżœ0.05 mm, ïżœ0.10 mm, ïżœ0.15 mm of the actual measured value, respectively.3. This work developed an Iterative Forward approach to redesign the Computer-Aided- Design model by reverse engineering using the trained machine learning models, allowing for compensation of print imperfection at the design stage, in advance of the first printing. The compensation algorithms with eight different sets of different parameters were evaluated. It has been proven that the Iterative Forward approach improved the geometric deviation of the predicted profiles by making compensation to the CAD model
Forum Bildverarbeitung 2020
Image processing plays a key role for fast and contact-free data acquisition in many technical areas, e.g., in quality control or robotics. These conference proceedings of the âForum Bildverarbeitungâ, which took place on 26.-27.11.202 in Karlsruhe as a common event of the Karlsruhe Institute of Technology and the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, contain the articles of the contributions
Image Registration Workshop Proceedings
Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research
Integrating passive ubiquitous surfaces into human-computer interaction
Mobile technologies enable people to interact with computers ubiquitously. This dissertation investigates how ordinary, ubiquitous surfaces can be integrated into human-computer interaction to extend the interaction space beyond the edge of the display. It turns out that acoustic and tactile features generated during an interaction can be combined to identify input events, the user, and the surface. In addition, it is shown that a heterogeneous distribution of different surfaces is particularly suitable for realizing versatile interaction modalities. However, privacy concerns must be considered when selecting sensors, and context can be crucial in determining whether and what interaction to perform.Mobile Technologien ermöglichen den Menschen eine allgegenwĂ€rtige Interaktion mit Computern. Diese Dissertation untersucht, wie gewöhnliche, allgegenwĂ€rtige OberflĂ€chen in die Mensch-Computer-Interaktion integriert werden können, um den Interaktionsraum ĂŒber den Rand des Displays hinaus zu erweitern. Es stellt sich heraus, dass akustische und taktile Merkmale, die wĂ€hrend einer Interaktion erzeugt werden, kombiniert werden können, um Eingabeereignisse, den Benutzer und die OberflĂ€che zu identifizieren. DarĂŒber hinaus wird gezeigt, dass eine heterogene Verteilung verschiedener OberflĂ€chen besonders geeignet ist, um vielfĂ€ltige InteraktionsmodalitĂ€ten zu realisieren. Bei der Auswahl der Sensoren mĂŒssen jedoch Datenschutzaspekte berĂŒcksichtigt werden, und der Kontext kann entscheidend dafĂŒr sein, ob und welche Interaktion durchgefĂŒhrt werden soll