Review of the mathematical foundations of data fusion techniques in surface metrology

The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed

Three-dimensional measurements with a novel technique combination of confocal and focus variation with a simultaneous scan

The most common optical measurement technologies used today for the three dimensional measurement of technical surfaces are Coherence Scanning Interferometry (CSI), Imaging Confocal Microscopy (IC), and Focus Variation (FV). Each one has its benefits and its drawbacks. FV will be the ideal technology for the measurement of those regions where the slopes are high and where the surface is very rough, while CSI and IC will provide better results for smoother and flatter surface regions. In this work we investigated the benefits and drawbacks of combining Interferometry, Confocal and focus variation to get better measurement of technical surfaces. We investigated a way of using Microdisplay Scanning type of Confocal Microscope to acquire on a simultaneous scan confocal and focus Variation information to reconstruct a three dimensional measurement. Several methods are presented to fuse the optical sectioning properties of both techniques as well as the topographical information. This work shows the benefit of this combination technique on several industrial samples where neither confocal nor focus variation is able to provide optimal results.Postprint (author's final draft

A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces

Optical instruments are widely used for precision surface measurement. However, the dynamic range of optical instruments, in terms of measurement area and resolution, is limited by the characteristics of the imaging and the detection systems. If a large area with a high resolution is required, multiple measurements need to be conducted and the resulting datasets needs to be stitched together. Traditional stitching methods use six degrees of freedom for the registration of the overlapped regions, which can result in high computational complexity. Moreover, measurement error increases with increasing measurement data. In this paper, a stitching method, based on a Gaussian process, image registration and edge intensity data fusion, is presented. Firstly, the stitched datasets are modelled by using a Gaussian process so as to determine the mean of each stitched tile. Secondly, the datasets are projected to a base plane. In this way, the three-dimensional datasets are transformed to two-dimensional (2D) images. The images are registered by using an (x, y) translation to simplify the complexity. By using a high precision linear stage that is integral to the measurement instrument, the rotational error becomes insignificant and the cumulative rotational error can be eliminated. The translational error can be compensated by the image registration process. The z direction registration is performed by a least-squares error algorithm and the (x, y, z) translational information is determined. Finally, the overlapped regions of the measurement datasets are fused together by the edge intensity data fusion method. As a result, a large measurement area with a high resolution is obtained. A simulated and an actual measurement with a coherence scanning interferometer have been conducted to verify the proposed method. The stitching result shows that the proposed method is technically feasible for large area surface measurement

IMAGE FUSION FOR MULTIFOCUS IMAGES USING SPEEDUP ROBUST FEATURES

The multi-focus image fusion technique has emerged as major topic in image processing in order to generate all focus images with increased depth of field from multi focus photographs. Image fusion is the process of combining relevant information from two or more images into a single image. The image registration technique includes the entropy theory. Speed up Robust Features (SURF), feature detector and Binary Robust Invariant Scalable Key points (BRISK) feature descriptor is used in feature matching process. An improved RANDOM Sample Consensus (RANSAC) algorithm is adopted to reject incorrect matches. The registered images are fused using stationary wavelet transform (SWT).The experimental results prove that the proposed algorithm achieves better performance for unregistered multiple multi-focus images and it especially robust to scale and rotation translation compared with traditional direct fusion method.  Â

Real-time multi-image vignetting and exposure correction for image stitching

Seamless image stitching depends not only on the accurate alignments of camera images, but also on the compensation of illumination inconsistencies. Even if two images are aligned perfectly, the seam is still visible if the images have a distinct vignetting or different exposure. Image stitching is used to expand the field of view, but a visible seam can lead to significant errors in subsequent visual perception tasks. As a result, we present a straightforward and accurate method for vignetting and exposure correction for stitched images. Firstly, we estimate the camera response function that maps irradiance to intensity. Then, the vignetting model is determined, which is applied to the irradiance images. After that, the exposure of the stitched images is corrected with the irradiance values at the seam. Finally, the irradiance is converted back into intensity using the camera response function. Our approach is evaluated using data recorded by our experimental vehicle and the public nuScenes dataset. Thereby, we test the performance of our method using the IoU of the histograms as well as the mean absolute error of the intensity values in the overlapping image regions. Further more, we demonstrate the real-time capability of our approach

3D garment digitisation for virtual wardrobe using a commodity depth sensor

5-Aminovaleric acid (5AVA) is an important five-carbon platform chemical that can be used for the synthesis of polymers and other chemicals of industrial interest. Enzymatic conversion of L-lysine to 5AVA has been achieved by employing lysine 2-monooxygenase encoded by the davB gene and 5-aminovaleramidase encoded by the davA gene. Additionally, a recombinant Escherichia coli strain expressing the davB and davA genes has been developed for bioconversion of L-lysine to 5AVA. To use glucose and xylose derived from lignocellulosic biomass as substrates, rather than L-lysine as a substrate, we previously examined direct fermentative production of 5AVA from glucose by metabolically engineered E. coli strains. However, the yield and productivity of 5AVA achieved by recombinant E. coli strains remain very low. Thus, Corynebacterium glutamicum, a highly efficient L-lysine producing microorganism, should be useful in the development of direct fermentative production of 5AVA using L-lysine as a precursor for 5AVA. Here, we report the development of metabolically engineered C. glutamicum strains for enhanced fermentative production of 5AVA from glucose.Various expression vectors containing different promoters and origins of replication were examined for optimal expression of Pseudomonas putida davB and davA genes encoding lysine 2-monooxygenase and delta-aminovaleramidase, respectively. Among them, expression of the C. glutamicum codon-optimized davA gene fused with His-Tag at its N-Terminal and the davB gene as an operon under a strong synthetic H promoter (plasmid p36davAB3) in C. glutamicum enabled the most efficient production of 5AVA. Flask culture and fed-batch culture of this strain produced 6.9 and 19.7\ua0g/L (together with 11.9\ua0g/L glutaric acid as major byproduct) of 5AVA, respectively. Homology modeling suggested that endogenous gamma-aminobutyrate aminotransferase encoded by the gabT gene might be responsible for the conversion of 5AVA to glutaric acid in recombinant C. glutamicum. Fed-batch culture of a C. glutamicum gabT mutant-harboring p36davAB3 produced 33.1\ua0g/L 5AVA with much reduced (2.0\ua0g/L) production of glutaric acid.Corynebacterium glutamicum was successfully engineered to produce 5AVA from glucose by optimizing the expression of two key enzymes, lysine 2-monooxygenase and delta-aminovaleramidase. In addition, production of glutaric acid, a major byproduct, was significantly reduced by employing C. glutamicum gabT mutant as a host strain. The metabolically engineered C. glutamicum strains developed in this study should be useful for enhanced fermentative production of the novel C5 platform chemical 5AVA from renewable resources