Coma measurement using a PSM and transmission image sensor

As feature size decreases, especially with the use of resolution enhancement technique, requirements for the coma aberrations in the projection lenses of the lithographic tools have become extremely severe. So, fast and accurate in situ measurement of coma is necessary. In the present paper, we present a new method for characterizing the coma aberrations in the projection lens using a phase-shifting mask and a transmission image sensor. By measuring the image positions at multiple NA and partial coherence settings, we are able to extract the coma aberration. The simulation results show that the accuracy of coma measurement increases approximately 20% compared to the previous straightforward measurement technique. (c) 2005 Elsevier GmbH. All rights reserved.

On-line learning of mutually orthogonal subspaces for face recognition by image sets.

We address the problem of face recognition by matching image sets. Each set of face images is represented by a subspace (or linear manifold) and recognition is carried out by subspace-to-subspace matching. In this paper, 1) a new discriminative method that maximises orthogonality between subspaces is proposed. The method improves the discrimination power of the subspace angle based face recognition method by maximizing the angles between different classes. 2) We propose a method for on-line updating the discriminative subspaces as a mechanism for continuously improving recognition accuracy. 3) A further enhancement called locally orthogonal subspace method is presented to maximise the orthogonality between competing classes. Experiments using 700 face image sets have shown that the proposed method outperforms relevant prior art and effectively boosts its accuracy by online learning. It is shown that the method for online learning delivers the same solution as the batch computation at far lower computational cost and the locally orthogonal method exhibits improved accuracy. We also demonstrate the merit of the proposed face recognition method on portal scenarios of multiple biometric grand challenge.

Retaining axial-lateral orthogonality in steered ultrasound data to improve image quality in reconstructed lateral displacement data

Ultrasound elastography tracks tissue displacements under small levels of compression to obtain images of strain, a mechanical property useful in the detection and characterization of pathology. Due to the nature of ultrasound beamforming, only tissue displacements in the direction of beam propagation, referred to as 'axial', are measured to high quality, although an ability to measure other components of tissue displacement is desired to more fully characterize the mechanical behavior of tissue. Previous studies have used multiple one-dimensional (1D) angled axial displacements tracked from steered ultrasound beams to reconstruct improved quality trans-axial displacements within the scan plane ('lateral'). We show that two-dimensional (2D) displacement tracking is not possible with unmodified electronically-steered ultrasound data, and present a method of reshaping frames of steered ultrasound data to retain axial-lateral orthogonality, which permits 2D displacement tracking. Simulated and experimental ultrasound data are used to compare changes in image quality of lateral displacements reconstructed using 1D and 2D tracked steered axial and steered lateral data. Reconstructed lateral displacement image quality generally improves with the use of 2D displacement tracking at each steering angle, relative to axial tracking alone, particularly at high levels of compression. Due to the influence of tracking noise, unsteered lateral displacements exhibit greater accuracy than axial-based reconstructions at high levels of applied strain. © 2011 SPIE.

2D PIV measurements in the near field of grid turbulence using stitched fields from multiple cameras

We present measurements of grid turbulence using 2D particle image velocimetry taken immediately downstream from the grid at a Reynolds number of Re M = 16500 where M is the rod spacing. A long field of view of 14M x 4M in the down- and cross-stream directions was achieved by stitching multiple cameras together. Two uniform biplanar grids were selected to have the same M and pressure drop but different rod diameter D and crosssection. A large data set (10 4 vector fields) was obtained to ensure good convergence of second-order statistics. Estimations of the dissipation rate ε of turbulent kinetic energy (TKE) were found to be sensitive to the number of meansquared velocity gradient terms included and not whether the turbulence was assumed to adhere to isotropy or axisymmetry. The resolution dependency of different turbulence statistics was assessed with a procedure that does not rely on the dissipation scale η. The streamwise evolution of the TKE components and ε was found to collapse across grids when the rod diameter was included in the normalisation. We argue that this should be the case between all regular grids when the other relevant dimensionless quantities are matched and the flow has become homogeneous across the stream. Two-point space correlation functions at x/M = 1 show evidence of complex wake interactions which exhibit a strong Reynolds number dependence. However, these changes in initial conditions disappear indicating rapid cross-stream homogenisation. On the other hand, isotropy was, as expected, not found to be established by x/M = 12 for any case studied. © Springer-Verlag 2012.

MCBoost: Multiple classifier boosting for perceptual co-clustering of images and visual features

We present a new co-clustering problem of images and visual features. The problem involves a set of non-object images in addition to a set of object images and features to be co-clustered. Co-clustering is performed in a way that maximises discrimination of object images from non-object images, thus emphasizing discriminative features. This provides a way of obtaining perceptual joint-clusters of object images and features. We tackle the problem by simultaneously boosting multiple strong classifiers which compete for images by their expertise. Each boosting classifier is an aggregation of weak-learners, i.e. simple visual features. The obtained classifiers are useful for object detection tasks which exhibit multimodalities, e.g. multi-category and multi-view object detection tasks. Experiments on a set of pedestrian images and a face data set demonstrate that the method yields intuitive image clusters with associated features and is much superior to conventional boosting classifiers in object detection tasks.

Multiple classifier boosting and tree-structured classifiers

Visual recognition problems often involve classification of myriads of pixels, across scales, to locate objects of interest in an image or to segment images according to object classes. The requirement for high speed and accuracy makes the problems very challenging and has motivated studies on efficient classification algorithms. A novel multi-classifier boosting algorithm is proposed to tackle the multimodal problems by simultaneously clustering samples and boosting classifiers in Section 2. The method is extended into an online version for object tracking in Section 3. Section 4 presents a tree-structured classifier, called Super tree, to further speed up the classification time of a standard boosting classifier. The proposed methods are demonstrated for object detection, tracking and segmentation tasks. © 2013 Springer-Verlag Berlin Heidelberg.

Tensile strength of UD-composite laminates with multiple holes

The residual strength of glass fibre reinforced vinyl-ester laminates with multiple holes was investigated through an experimental programme. Different types of structured hole patterns and hole densities were investigated and analysed using digital image correlation strain measuring technique. Three different failure modes could be observed when the hole patterns and the hole densities were a altered. These three failure modes were used as the foundation for a simple yet effective analytical model in order to predict the residual strength of damaged composite specimens. Finally, a number of laminates with randomly distributed holes were tested experimentally. The analytical model can predict the failure mode and failure strength of the experiments with sufficiently good fidelity. © 2010 Elsevier Ltd.

Multiple energy transfers in rare earth complex-doped SiO2 spheres

Silica spheres doped with Eu(TTFA)(3) and/or Sm(TTFA)(3) were synthesized by using the modified Stober method. The transmission electron microscope image reveals that the hybrid spheres have smooth surfaces and an average diameter of about 210 nm. Fluorescence spectrometer was used to analyze the fluorescence properties of hybrid spheres. The results show that multiple energy transfer processes are simultaneously achieved in the same samples co-doped with Eu (TTFA)(3) and Sm(TTFA)(3), namely between the ligand and Eu3+ ion, the ligand and Sm3+ ion, and Sm3+ ion and Eu3+, ion. Energy transfer of Sm3+-> Eu3+, in the hybrid spheres leads to fluorescence enhancement of Eu3+ emission by approximately an order of magnitude. The lifetimes of the hybrid spheres were also measured.

Partially Supervised Neighbor Embedding for Example-Based Image Super-Resolution

Neighbor embedding algorithm has been widely used in example-based super-resolution reconstruction from a single frame, which makes the assumption that neighbor patches embedded are contained in a single manifold. However, it is not always true for complicated texture structure. In this paper, we believe that textures may be contained in multiple manifolds, corresponding to classes. Under this assumption, we present a novel example-based image super-resolution reconstruction algorithm with clustering and supervised neighbor embedding (CSNE). First, a class predictor for low-resolution (LR) patches is learnt by an unsupervised Gaussian mixture model. Then by utilizing class label information of each patch, a supervised neighbor embedding is used to estimate high-resolution (HR) patches corresponding to LR patches. The experimental results show that the proposed method can achieve a better recovery of LR comparing with other simple schemes using neighbor embedding.

Multiple melting and crystallization behavior of nylon 1212

The wide-angle X-ray diffraction (WAXD) patterns of isothermally crystallized Nylon 1212 show that gamma-form crystals form below 90 degrees C and the alpha-form crystals call exist above 140 degrees C. In the temperature range of 90-140 degrees C, the a-form gamma-form crystals coexist. Variable-temperature WAXD exhibits that the nylon 1212 gamma-form does not show crystal and transition on heating, while a-form isothermally crystallized at 160 degrees C exhibits Brill transition at a little higher than 180 degrees C on heating. The multiple melting behaviors of Nylon 1212 isothermally crystallized from melt come from a complex mechanism of different crystal structures, dual lamellar population and melting-recrystallization. In polarized optical microscope (POM) observations, Nylon 1212 isothermally crystallized at 175 degrees C shows the ringed banded spherulites. However, at temperatures below 160 degrees C the ringed handed image disappears, and cross-extinct spherulites are formed.

Monitoring Activities from Multiple Video Streams: Establishing a Common Coordinate Frame

Passive monitoring of large sites typically requires coordination between multiple cameras, which in turn requires methods for automatically relating events between distributed cameras. This paper tackles the problem of self-calibration of multiple cameras which are very far apart, using feature correspondences to determine the camera geometry. The key problem is finding such correspondences. Since the camera geometry and photometric characteristics vary considerably between images, one cannot use brightness and/or proximity constraints. Instead we apply planar geometric constraints to moving objects in the scene in order to align the scene"s ground plane across multiple views. We do not assume synchronized cameras, and we show that enforcing geometric constraints enables us to align the tracking data in time. Once we have recovered the homography which aligns the planar structure in the scene, we can compute from the homography matrix the 3D position of the plane and the relative camera positions. This in turn enables us to recover a homography matrix which maps the images to an overhead view. We demonstrate this technique in two settings: a controlled lab setting where we test the effects of errors in internal camera calibration, and an uncontrolled, outdoor setting in which the full procedure is applied to external camera calibration and ground plane recovery. In spite of noise in the internal camera parameters and image data, the system successfully recovers both planar structure and relative camera positions in both settings.