Complete Processing Chain Research Articles

Image Visualization and Restoration by Curvature Motions

This paper presents a review, analysis, and comparison of numerical methods implementing the curvature motion and the affine curvature motion for two-dimensional (2D) images, shapes, and curves. These curvature scale spaces allow, in principle, one to compute an accurate multiscale curvature in digital images. The fastest and most invariant of them can be used in a complete image processing chain. This numerical chain simulates the accurate subpixel evolution of an image by mean curvature motion or by affine invariant curvature motion. To do so, it lets all the level lines of the image evolve by curvature shortening (of affine shortening), computes the image curvature directly on the smoothed level lines, and reconstructs the evolved image and its curvatures in an intrinsic, grid independent representation. The paper describes a careful implementation of this chain and analyzes its effects on many examples. The microscopic visualization of an image curvature map reveals after processing many image details. This image process improves graphic images and gets rid of compression and aliasing effects. It also gives an accurate tool to explore the validity of Attneave’s and Julesz’s theories on shape perception and texture discrimination. The “curvature microscope’’ runs online for any image at http://www.ipol.im/pub/algo/cmmm_image_curvature_microscope/.

Alternative method for angular rate determination within the GOCE gradiometer processing

The most crucial part of the GOCE gradiometer processing is, besides the internal calibration of the gradiometer, the determination of the satellite’s inertial angular rate. This paper describes a new method for the angular rate determination. It is based on the stochastic properties of the GOCE star sensors and the gradiometer. The attitude information of both instrument types is combined at the level of angular rates. The combination is done in the spectral domain by Wiener filtering, and thus using an optimal relative weighting of the star sensor and gradiometer attitude information. Since the complete processing chain from raw measurements to gravity field solutions is performed, the results are not only analyzed at the level of gravity gradients, but also of gravity field solutions. Compared to the nominal method, already the resulting gravity gradients show a significantly improved performance for the frequencies (mainly) below the gradiometer measurement bandwidth. This can be verified by analysis of the gravity gradient trace. The improvement is propagated to the level of gravity field models, where a better accuracy can be observed for selected groups of coefficients at characteristic bands at orders k × 16, with integer k, up to high harmonic degrees.

A complete processing chain for ship detection using optical satellite imagery

Ship detection from remote sensing imagery is a crucial application for maritime security, which includes among others traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. In the framework of a European integrated project Global Monitoring for Environment and Security (GMES) Security/Land and Sea Integrated Monitoring for European Security (LIMES), we developed an operational ship detection algorithm using high spatial resolution optical imagery to complement existing regulations, in particular the fishing control system. The automatic detection model is based on statistical methods, mathematical morphology and other signal-processing techniques such as the wavelet analysis and Radon transform. This article presents current progress made on the detection model and describes the prototype designed to classify small targets. The prototype was tested on panchromatic Satellite Pour l'Observation de la Terre (SPOT) 5 imagery taking into account the environmental and fishing context in French Guiana. In terms of automatic detection of small ship targets, the proposed algorithm performs well. Its advantages are manifold: it is simple and robust, but most of all, it is efficient and fast, which is a crucial point in performance evaluation of advanced ship detection strategies.

JULIDE: a software tool for 3D reconstruction and statistical analysis of autoradiographic mouse brain sections.

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

Underwater acoustic localization for small submersibles

AbstractThis article discusses the complete processing chain of a high‐precision as well as robust underwater localization method. Range and azimuth as well as relative heading are determined for ranges up to 90 m. For ranges up to 10 m the measured precision is 0.05 m for range, 2 deg for direction, and 5 deg for heading of neighboring vehicles. The system is also designed to be deployable in swarms of vehicles as acoustic localization signals are separated by time slots and maximum length sequence (MLS) signatures. The proposed method is based on the consequent exploitation of MLS broadband signal characteristics and the exploration of several methods for each vehicle to estimate ranges, azimuths, and headings of neighboring vehicles. An existing radio‐based swarm communication system provides additional support and leads to enhanced measurement precision and interference robustness. The capabilities and limitations of the proposed systems are experimentally determined and discussed. © 2010 Wiley Periodicals, Inc.

Automatic Level Control for Video Cameras towards HDR Techniques

We give a comprehensive overview of the complete exposure processing chain for video cameras. For each step of the automatic exposure algorithm we discuss some classical solutions and propose their improvements or give new alternatives. We start by explaining exposure metering methods, describing types of signals that are used as the scene content descriptors as well as means to utilize these descriptors. We also discuss different exposure control types used for the control of lens, integration time of the sensor, and gain control, such as a PID control, precalculated control based on the camera response function, and propose a new recursive control type that matches the underlying image formation model. Then, a description of commonly used serial control strategy for lens, sensor exposure time, and gain is presented, followed by a proposal of a new parallel control solution that integrates well with tone mapping and enhancement part of the image pipeline. Parallel control strategy enables faster and smoother control and facilitates optimally filling the dynamic range of the sensor to improve the SNR and an image contrast, while avoiding signal clipping. This is archived by the proposed special control modes used for better display and correct exposure of both low-dynamic range and high-dynamic range images. To overcome the inherited problems of limited dynamic range of capturing devices we discuss a paradigm of multiple exposure techniques. Using these techniques we can enable a correct rendering of difficult class of high-dynamic range input scenes. However, multiple exposure techniques bring several challenges, especially in the presence of motion and artificial light sources such as fluorescent lights. In particular, false colors and light-flickering problems are described. After briefly discussing some known possible solutions for the motion problem, we focus on solving the fluorescence-light problem. Thereby, we propose an algorithm for the detection of fluorescent lights from the image itself and define a set of remedial actions, to minimize false color and light-flickering problems.

Simulation of Gas and Spray Quenching during Extrusion of Aluminium Alloys

After the extrusion process most aluminium alloy profiles don´t satisfy the necessary strength requirements. An increase of strength can be obtained by age hardening of hardenable aluminium alloys. Age hardening includes the three steps of solution annealing, quenching and aging and is usually carried out in a separate process after extrusion. The integration of the sub-steps solution annealing and quenching in the extrusion process results in a marked reduction of the complete process chain. The applicability of this integration depends primarily on the quenching power of the cooling module and on the quench sensitivity of the aluminium alloy. Using the finite element method the non-steady-state process of quenching the profiles after leaving the extrusion press has been simulated. The boundary conditions for quenching are varied for a gas nozzle field and a spray cooling using heat transfer coefficients based on experiments. The simulation results support the design of gas nozzle fields or spray cooling for the extrusion process of different aluminium alloys.

Monitoring genetically modified soybean along the industrial soybean oil extraction and refining processes by polymerase chain reaction techniques

In the present work, the extraction and detection of DNA along a complete industrial soybean oil processing chain was described to monitor the presence of Roundup Ready® (RR) soybean. The analysed samples comprised all the steps prior to industrial oil extraction, namely, raw, cracked, laminated and expanded seeds, and the defatted flour as a sub-product. The samples collected at the refining unit included the crude oil, degummed/neutralised, washed, bleached and deodorised oil, as final product. The amplification of soybean lectin gene by end-point polymerase chain reaction (PCR) was successfully achieved in all the steps of extraction and refining processes, until the fully refined soybean oil. The amplification of RR soybean by PCR assays using event-specific primers was also achieved for all the extraction and refining steps, except for the intermediate steps of refining (neutralisation, washing and bleaching) possibly due to sample instability. The real-time PCR assays using specific probes confirmed all the results and proved that it is possible to detect and quantify genetically modified organisms in the fully refined soybean oil. To our knowledge, this has never been reported before and represents an important accomplishment regarding the traceability of genetically modified organisms in refined oils.

Digital Data Storage on Microfilm – The MILLENIUM Project: Signal and Information Processing

Digital data storage on microfilm is a highly promising technology for migration-free long-term storage of digital information. The lifetime of the medium microfilm is estimated to be 500 years under appropriate storage conditions. Towards a practical implementation of this concept, the MILLENIUM project was initiated in 2006. The project is funded by the German Federal Ministry of Economics and Technology (BMWi) and is conducted by two research institutions as well as several small and medium-sized enterprises. This paper reflects project achievements with respect to signal and information processing. The complete processing chain for digital data is described. Important parts of this chain are identified and discussed in more detail. Some focus is on frame structures and data organization as well as synchronization, error correction and storage capacity. The developed concepts are ready for implementation.

Assessment of Polarimetric SAR Interferometry for Improving Ship Classification based on Simulated Data.

This paper uses a complete and realistic SAR simulation processing chain, GRECOSAR, to study the potentialities of Polarimetric SAR Interferometry (POLInSAR) in the development of new classification methods for ships. Its high processing efficiency and scenario flexibility have allowed to develop exhaustive scattering studies. The results have revealed, first, vessels' geometries can be described by specific combinations of Permanent Polarimetric Scatterers (PePS) and, second, each type of vessel could be characterized by a particular spatial and polarimetric distribution of PePS. Such properties have been recently exploited to propose a new Vessel Classification Algorithm (VCA) working with POLInSAR data, which, according to several simulation tests, may provide promising performance in real scenarios. Along the paper, explanation of the main steps summarizing the whole research activity carried out with ships and GRECOSAR are provided as well as examples of the main results and VCA validation tests. Special attention will be devoted to the new improvements achieved, which are related to simulations processing a new and highly realistic sea surface model. The paper will show that, for POLInSAR data with fine resolution, VCA can help to classify ships with notable robustness under diverse and adverse observation conditions.

Quality assurance of the Brewer spectral UV measurements in Finland

Abstract. The quality assurance of the two Brewer spectrophotometers of the Finnish Meteorological Institute is discussed in this paper. The complete data processing chain from raw signal to high quality spectra is presented. The quality assurance includes daily maintenance, laboratory characterizations, calculation of long-term spectral responsivity, data processing and quality assessment. The cosine correction of the measurements is based on a new method, and is included in the data processing software. The results showed that the actual cosine correction factor of the two Finnish Brewers can vary between 1.08–1.13 and 1.08–1.12, respectively, depending on the sky radiance distribution and wavelength. The temperature characterization showed a linear temperature dependence between the instruments' internal temperature and the photon counts per cycle, and a temperature correction was used for correcting the measurements. The long-term spectral responsivity was calculated using the time series of several lamps using two slightly different methods. The long-term spectral responsivity was scaled to the irradiance scale of the Helsinki University of Technology (HUT) for the whole of the measurement time-periods 1990–2006 and 1995–2006 for Sodankylä and Jokioinen, respectively. Both Brewers have participated in many international spectroradiometer comparisons, and have shown good stability. The differences between the Brewers and the portable reference spectroradiometer QASUME have been within 5% during 2002–2007.

Quantification of uncertainties in flood risk assessments

By a common definition, flood risk assessments are comprised of two parts: a hazard and vulnerability assessment. The hazard assessment investigates the extent and magnitude of usually large flood events, which are associated to a certain exceedance probability, whereas the vulnerability part assesses the impact of the flooding on specified targets, e.g., building, people or infrastructure. Being inherently speculative flood risk assessments should always be accompanied by an uncertainty assessment in order to assist consequent decision properly. In this paper a dynamic‐probabilistic method is proposed, which enables a cumulated flood risk assessment of a complete river reach considering dike failures at all dike locations. The model uses simple but computational efficient modules to simulate the complete process chain of flooding. These modules are embedded into a Monte Carlo framework thus enabling a risk assessment which is physically based thus mapping the real flooding process, and which is also probabilistic and not based on scenarios. The model also provides uncertainty estimates by quantifying various epistemic uncertainty sources of the hazard as well as the vulnerability part in a second layer of Monte Carlo simulations. These uncertainty estimates are associated to defined return intervals of the model outputs, i.e., the derived flood frequencies at the end of the reach and the risk curves for the complete reach, thus providing valuable information for the interpretation of the results. By separating single uncertainty sources a comparison of the contribution of different uncertainty sources to the overall predictive uncertainty in terms of derived flood frequencies and monetary risks could be performed. This revealed that the major uncertainties are extreme value statistics, resp. the length of the data series used and the discharge‐stage relation used for the transformation of discharge into water levels in the river.

Exergy: Its Potential and Limitations in Environmental Science and Technology

New technologies, either renewables-based or not, are confronted with both economic and technical constraints. Their development takes advantage of considering the basic laws of economics and thermodynamics. With respect to the latter, the exergy concept pops up. Although its fundamentals, that is, the Second Law of Thermodynamics, were already established in the 1800s, it is only in the last years that the exergy concept has gained a more widespread interest in process analysis, typically employed to identify inefficiencies. However, exergy analysis today is implemented far beyond technical analysis; it is also employed in environmental, (thermo)economic, and even sustainability analysis of industrial systems. Because natural ecosystems are also subjected to the basic laws of thermodynamics, it is another subject of exergy analysis. After an introduction on the concept itself, this review focuses on the potential and limitations of the exergy conceptin (1) ecosystem analysis, utilized to describe maximum storage and maximum dissipation of energy flows (2); industrial system analysis: from single process analysis to complete process chain analysis (3); (thermo)economic analysis, with extended exergy accounting; and (4) environmental impact assessment throughout the whole life cycle with quantification of the resource intake and emission effects. Apart from technical system analysis, it proves that exergy as a tool in environmental impact analysis may be the most mature field of application, particularly with respect to resource and efficiency accounting, one of the major challenges in the development of sustainable technology. Far less mature is the exergy analysis of natural ecosystems and the coupling with economic analysis, where a lively debate is presently going on about the actual merits of an exergy-based approach.

Key performance indicators for sheet metal forming processes

Sheet metal forming is a typical process in the manufacturing industry. It is well established, e.g. for the production of car body components or consumer goods. Suppliers of Original Equipment Manufacturers (OEM) produce a wide range of products in different dimensions, varying batch sizes and geometries. For the production process itself, there are multiple configurations regarding the selection of technologies, machines and tools to be used. In order to meet the market’s requirements and to be highly competitive, the complete process chain needs to be optimized. The main challenge for the optimization of the process chain is the simultaneous consideration of technical and organizational parameters. The relevant key performance indicators (KPIs) have to be identified and used to support the decision-making process for production planning purposes. In this article a method to identify the relevant KPI is described and relevant indicators were proposed.

Real-time hand posture recognition using range data

A hand posture recognition system using 3D data is described. The system relies on a novel 3D sensor that generates a dense range image of the scene. The main advantage of the proposed system, compared to other gesture recognition techniques, is the capability for robust unconstrained recognition of complex hand postures such as those encountered in sign language alphabets. This is achieved by explicitly utilizing 3D hand geometry. Moreover, the proposed approach does not rely on color information, and guarantees robust segmentation of the hand under varying illumination conditions, and scene content. Several novel 3D image analysis algorithms are presented, covering the complete processing chain: 3D image acquisition, arm segmentation, hand–forearm segmentation, hand pose estimation, 3D feature extraction, and gesture classification. The proposed system is extensively evaluated.

Design of Experiments for Performance Evaluation and Parameter Tuning of a Road Image Processing Chain

Tuning a complete image processing chain (IPC) is not a straightforward task. The first problem to overcome is the evaluation of the whole process. Until now researchers have focused on the evaluation of single algorithms based on a small number of test images and ad hoc tuning independent of input data. In this paper, we explain how the design of experiments applied on a large image database enables statistical modeling for IPC significant parameter identification. The second problem is then considered: how can we find the relevant tuning and continuously adapt image processing to input data? After the tuning of the IPC on a typical subset of the image database using numerical optimization, we develop an adaptive IPC based on a neural network working on input image descriptors. By testing this approach on an IPC dedicated-to-road obstacle detection, we demonstrate that this experimental methodology and software architecture can ensure continuous efficiency. The reason is simple: the IPC is globally optimized, from a large number of real images and with adaptive processing of input data.

High Quality Magnesium Sheets for Automotive Applications

In order to make magnesium sheets a competitive material alternative for highly sophisticated light-weight constructions the complete process chain for their production has to be investigated. In laboratory scale new alloys, casting techniques and optimized rolling and heat treatment schedules have been developed. At the Institute for Metal Forming and Metal Forming Machine Tools (IFUM) the forming capacity of magnesium sheets has been investigated. Derived from the strict quality requirements of e.g. the automotive industry, testing methods concerning mechanical properties, corrosion resistance and surface quality have been developed. It has been shown that the controlled development of a suited microstructure is the key factor for ensuring the requested product properties. Together with research and manufacturing partners the results were transferred to industrial practice and a closed loop process chain for the production of high quality magnesium sheets has been established.

Comparison of Material Behavior and Economic Effects of Cold and High Temperature Forming Technologies Applied to High-Strength Steels

The focus of forming high-strength steel at elevated temperature is to improve its forming properties like elongation and to reduce the power requirements during the forming process in opposite to cold forming. Because of the undefined and large spring-back effects parts made by cold forming are not able to achieve the demanded dimensional accuracy, which is necessary for laser welding operations in car body assembly. The reduction of the spring-back behavior is another advantage of the temperature controlled forming technology. On the other side the forming at elevated temperatures requires increased costs for forming tools and tempering equipment. For a fundamental evaluation of this technology, expenditures for the complete process chain have to be considered.

High resolution spaceborne INSAR simulation with extended scenes

The inverse-EETF4 (extended exact transfer function 4th order) is used to simulate raw data and a complete INSAR processing chain for high squint has been developed. Phase differences for a spaceborne INSAR geometry are estimated and used as input to the inverse-EETF4 and then the simulated raw data are processed with EETF4. The standard deviation of the flattened interferogram is only a few degrees. The inverse-EETF4 is used to simulate extended SAR raw data from IKONOS images. The standard deviation of the auto-interferogram generated from those data is a few tenths of a degree. The simulations have been done with squint up to 40°, range block size of 1100 pixels and spatial resolution around 0.3 m. The inverse-EETF4 and EETF4 processing is performed by generation of discontinuous raw data which makes it possible to cope with very large range migration.

A model for the generation and evaluation of integrated manufacturing solutions for powertrain components

The vision to reduce secondary processing times dramatically has become a high priority in modern manufacturing enterprises. It is being realized that such improvements rely not only on the optimization of single processes but also on the layout optimization of the complete process chain. This is reflected in the increasing efforts by machine manufacturers to integrate multiple processing technologies into machining centres, thus shortening the process chains and reducing the overall lead-time. The purpose of the work described within is to develop a model that supports the user in identifying and evaluating potential integrated process chains. The model incorporates multicriteria analysis and net-present-value methodologies that enable assessment of the relative technological and economical advantages of the integrated manufacturing alternatives when compared to the conventional/ existing process chain. A case study undertaken that assessed whether laser hardening is a viable alternative for induction hardening for a particular powertrain component illustrates a particular instance in which the model was used.