G-ID: identifying 3D Prints using slicing parameters

We present G-ID, a method that utilizes the subtle patterns left by the 3D printing process to distinguish and identify objects that otherwise look similar to the human eye. The key idea is to mark different instances of a 3D model by varying slicing parameters that do not change the model geometry but can be detected as machine-readable differences in the print. As a result, G-ID does not add anything to the object but exploits the patterns appearing as a byproduct of slicing, an essential step of the 3D printing pipeline. We introduce the G-ID slicing & labeling interface that varies the settings for each instance, and the G-ID mobile app, which uses image processing techniques to retrieve the parameters and their associated labels from a photo of the 3D printed object. Finally, we evaluate our method’s accuracy under different lighting conditions, when objects were printed with different filaments and printers, and with pictures taken from various positions and angles

Multispectral photography for earth resources

A guide for producing accurate multispectral results for earth resource applications is presented along with theoretical and analytical concepts of color and multispectral photography. Topics discussed include: capabilities and limitations of color and color infrared films; image color measurements; methods of relating ground phenomena to film density and color measurement; sensitometry; considerations in the selection of multispectral cameras and components; and mission planning

Information embedding and retrieval in 3D printed objects

Deep learning and convolutional neural networks have become the main tools of computer vision. These techniques are good at using supervised learning to learn complex representations from data. In particular, under limited settings, the image recognition model now performs better than the human baseline. However, computer vision science aims to build machines that can see. It requires the model to be able to extract more valuable information from images and videos than recognition. Generally, it is much more challenging to apply these deep learning models from recognition to other problems in computer vision. This thesis presents end-to-end deep learning architectures for a new computer vision field: watermark retrieval from 3D printed objects. As it is a new area, there is no state-of-the-art on many challenging benchmarks. Hence, we first define the problems and introduce the traditional approach, Local Binary Pattern method, to set our baseline for further study. Our neural networks seem useful but straightfor- ward, which outperform traditional approaches. What is more, these networks have good generalization. However, because our research field is new, the problems we face are not only various unpredictable parameters but also limited and low-quality training data. To address this, we make two observations: (i) we do not need to learn everything from scratch, we know a lot about the image segmentation area, and (ii) we cannot know everything from data, our models should be aware what key features they should learn. This thesis explores these ideas and even explore more. We show how to use end-to-end deep learning models to learn to retrieve watermark bumps and tackle covariates from a few training images data. Secondly, we introduce ideas from synthetic image data and domain randomization to augment training data and understand various covariates that may affect retrieve real-world 3D watermark bumps. We also show how the illumination in synthetic images data to effect and even improve retrieval accuracy for real-world recognization applications

Toward Real-Time Video-Enhanced Augmented Reality for Medical Visualization and Simulation

In this work we demonstrate two separate forms of augmented reality environments for use with minimally-invasive surgical techniques. In Chapter 2 it is demonstrated how a video feed from a webcam, which could mimic a laparoscopic or endoscopic camera used during an interventional procedure, can be used to identify the pose of the camera with respect to the viewed scene and augment the video feed with computer-generated information, such as rendering of internal anatomy not visible beyond the image surface, resulting in a simple augmented reality environment. Chapter 3 details our implementation of a similar system to the one previously mentioned, albeit with an external tracking system. Additionally, we discuss the challenges and considerations for expanding this system to support an external tracking system, specifically the Polaris Spectra optical tracker. Because of the relocation of the tracking origin to a point other than the camera center, there is an additional registration step necessary to establish the position of all components within the scene. This modification is expected to increase accuracy and robustness of the system

2D-barcode for mobile devices

2D-barcodes were designed to carry significantly more data than its 1D counterpart. These codes are often used in industrial information tagging applications where high data capacity, mobility, and data robustness are required. Wireless mobile devices such as camera phones and Portable Digital Assistants (PDAs) have evolved from just a mobile voice communication device to what is now a mobile multimedia computing platform. Recent integration of these two mobile technologies has sparked some interesting applications where 2D-barcodes work as visual tags and/or information source and camera phones performs image processing tasks on the device itself. One of such applications is hyperlink establishment. The 2D symbol captured by a camera phone is decoded by the software installed in the phone. Then the web site indicated by the data encoded in a symbol is automatically accessed and shown in the display of the camera phone. Nonetheless, this new mobile applications area is still at its infancy. Each proposed mobile 2D-barcode application has its own choice of code, but no standard exists nor is there any study done on what are the criteria for setting a standard 2D-barcode for mobile phones. This study intends to address this void. The first phase of the study is qualitative examination. In order to select a best standard 2D-barcode, firstly, features desirable for a standard 2D-barcode that is optimized for the mobile phone platform are identified. The second step is to establish the criteria based on the features identified. These features are based on the operating limitations and attributes of camera phones in general use today. All published and accessible 2D-barcodes are thoroughly examined in terms of criteria set for the selection of a best 2D-barcode for camera phone applications. In the second phase, the 2D-barcodes that have higher potential to be chosen as a standard code are experimentally examined against the three criteria: light condition, distance, whether or not a 2D-barcode supports VGA resolution. Each sample 2D-barcode is captured by a camera phone with VGA resolution and the outcome is tested using an image analysis tool written in the scientific language called MATLAB. The outcome of this study is the selection of the most suitable 2D-barcode for applications where mobile devices such as camera phones are utilized

Methods for evaluating geometric distortion in magnetic resonance imaging

Abstract. Geometric distortions and spatial inaccuracies in magnetic resonance imaging are an important concern especially in image-guided high accuracy operations, such as radiotherapy or stereotactic surgeries. Geometric distortions in the images are in principle caused by erroneous spatial encoding of the signal echo. Errors in the spatial encoding are caused by different physical factors, such as static field inhomogeneity, gradient field nonlinearities, chemical shift, and magnetic susceptibility. The distortion shifts can be quantitatively evaluated as the amount of distance or pixels that a signal source has shifted in the mapping from real space to the image space. By studying the distortions and the causing mechanisms, corrective measures can be taken to minimize spatial errors in the images. In this thesis the geometric distortions of one MRI scanner are evaluated with four different grid phantom objects. The scanner was a 3 Tesla scanner at the Oulu University Hospital. The phantoms included two commercial readily available MRI quality assurance phantoms and two in-house produced prototype phantoms. The methods consisted of imaging the phantoms with different two- and three- dimensional sequences. Image and distortion analysis was performed with one commercial distortion check software for the respective commercial phantom, and with an in-house developed Matlab program for all four phantoms. Results for the magnitude and direction of the distortion as a function of distance from the scanner isocenter were acquired. Three-dimensional distortion shifts up 4 mm within a radius of 200 mm from the isocenter were measured, with occasional shifts up to 9 mm between 100 and 200 mm from the isocenter. Distortion field maps and contour plots produced with both analysis methods seemed to be in accordance with each other, and the geometry and behaviour of the field was found to be as expected. As to the prototype phantoms, a result with respect to the grid density was found. A 5 mm grid separation was too dense with respect to the achievable resolution for the Matlab analysis script to function, or more generally for any distortion check at all.Tiivistelmä. Magneettikuvien geometriset vääristymät ja epätarkkuudet ovat tärkeitä huomioon otettavia asioita erityisesti sädehoitoihin tai kirurgisiin operaatioihin liittyvissä kuvantamisissa. Kuvien vääristymät aiheutuvat virheistä signaalien paikkakoodauksessa. Paikkakoodaukseen aiheutuu virheitä eri fysikaalisista tekijöistä, kuten staattisen magneettikentän epähomogeenisuuksista, gradienttikenttien epälineaarisuuksista, kemiallisesta siirtymästä tai magneettisesta suskeptibiliteetistä. Geometrinen vääristymä voidaan määrittää kvantitatiivisesti tutkimalla signaalin paikan siirtymää kuvauksessa todellisesta koordinaatistosta, eli kuvattavasta kohteesta, kuvan koordinaatistoon. Kuvia voidaan myös korjata vääristymien osalta tutkimalla vääristymien luonnetta ja niiden aiheuttajia. Tässä tutkielmassa tutkittiin Oulun yliopistollisen sairaalan yhden 3 Teslan kenttävoimakkuuden magneettikuvauslaitteen geometrista vääristymää. Kuvauksissa käytettiin neljää erilaista fantomia, kahta valmista kaupallisesti saatavilla olevaa sekä kahta kokeellista prototyyppiä. Fantomeita kuvattiin eri kaksi- ja kolmiulotteisilla kuvaussekvensseillä. Kuva- ja vääristymäanalyysiä varten käytettiin yhtä kaupallista ohjelmaa, joka on tarkoitettu sitä vastaavalle fantomille, sekä itse sairaalassa kehitettyä Matlab-pohjaista ohjelmaa. Mittausten perusteella saatiin kvantitatiiviset tulokset vääristymän suuruudelle ja suunnalle, etäisyyden funktiona skannerin keskipisteestä. Kolmiulotteisten vääristymien suuruudet olivat 4 mm tai alle 200 mm säteelle asti, suurimpien yksittäisten vääristymien ollessa noin 9 mm tai alle 100 mm ja 200 mm etäisyyksien välillä. Molemmilla analyysiohjelmilla vääristymien suuntien perusteella luodut vektorikentät olivat toistensa mukaisia ja vääristymän käyttäytyminen vaikutti odotetulta. Prototyyppifantomien suhteen päädyttiin tulokseen, jonka mukaan 5 mm ruudukko oli liian tiheä suhteessa resoluutioon, eikä Matlab-pohjainen analyysi toiminut. Tarpeeksi leveä ruudukko oli siten oleellinen osa vääristymän määrittämistä

Currency security and forensics: a survey

By its definition, the word currency refers to an agreed medium for exchange, a nation’s currency is the formal medium enforced by the elected governing entity. Throughout history, issuers have faced one common threat: counterfeiting. Despite technological advancements, overcoming counterfeit production remains a distant future. Scientific determination of authenticity requires a deep understanding of the raw materials and manufacturing processes involved. This survey serves as a synthesis of the current literature to understand the technology and the mechanics involved in currency manufacture and security, whilst identifying gaps in the current literature. Ultimately, a robust currency is desire