Elliptical Objects Research Articles

Viscoplastic elliptical objects impacting a solid surface

This theoretical and numerical study focuses on the physical mechanism driving the spreading of viscoplastic elliptical millimetric/centimetric objects after they impact a solid surface under no-slip conditions. The two-dimensional impacting objects are described as Bingham fluids. The two-dimensional numerical simulations are based on a variational multi-scale approach devoted to multiphase non-Newtonian fluid flows. The obtained results are analyzed considering the spreading dynamics, energy budgets and scaling laws. They show that, under negligible capillary effects, the impacting kinetic energy of the elliptical objects is dissipated through viscoplastic effects during the spreading process, giving rise to three flow regimes: inertio-viscous, inertio-plastic, and mixed inertio-visco-plastic. These regimes are strongly affected by the initial aspect ratio of the impacting objects, which reveals the possibility of using morphology to control spreading. Finally, the results are summarized in a diagram linking the object's maximum spreading and spreading time with different spreading regimes through a single dimensionless parameter called impact number.

Lagrangian Solution of Schwarzschild-like Metric for an ‎Elliptical Object

Lagrangian method applied as well as tensor method, for a linear transformed geodesic line element of Schwarzschild-like The ‎Lagrangian method was applied for a linearly transformed geodesic line element of a Schwarzschild-like solution instead of ‎the tensor method. The solution shows that it is not only valid for spherical objects but also it is more comprehensive for ‎elliptical celestial objects. Two types of kinetic and potential energy are the basis of the calculation. Hamiltonian and ‎Lagrangian equality show that the problem has no potential energy. With this transformed geodesic line element, we obtained ‎a new coefficient for the meridional advance of an experimental particle in Schwarzschild spacetime in terms of period, ‎eccentricity, and mean distance. This new perigee equation is not only valid for the Schwarzschild metric (for a spherical ‎object), but also more accurate for the Schwarzschild-like metric (for elliptical objects).‎

Lagrangian Solution of Schwarzschild-like Metric for an ‎Elliptical Object

Lagrangian method applied as well as tensor method, for a linear transformed geodesic line element of Schwarzschild-like The ‎Lagrangian method was applied for a linearly transformed geodesic line element of a Schwarzschild-like solution instead of ‎the tensor method. The solution shows that it is not only valid for spherical objects but also it is more comprehensive for ‎elliptical celestial objects. Two types of kinetic and potential energy are the basis of the calculation. Hamiltonian and ‎Lagrangian equality show that the problem has no potential energy. With this transformed geodesic line element, we obtained ‎a new coefficient for the meridional advance of an experimental particle in Schwarzschild spacetime in terms of period, ‎eccentricity, and mean distance. This new perigee equation is not only valid for the Schwarzschild metric (for a spherical ‎object), but also more accurate for the Schwarzschild-like metric (for elliptical objects).‎

Hydrodynamics of an Elliptical Squirmer

In this paper the propulsion of elliptical objects (called squirmers) by imposed tangential velocity along the surface is studied. For a symmetric velocity distribution (a neutral squirmer), pushers (increased tangential velocity on the downstream side of the ellipse) and pullers (increased tangential velocity on the upstream side of the ellipse), the hydrodynamic characteristics, are simulated numerically using the immersed boundary-lattice Boltzmann method. The accuracy of the numerical scheme and code are validated. The effects of Reynolds number (Re) and squirmer aspect ratio (AR) on the velocity u*, power expenditure P* and hydrodynamic efficiency η of the squirmer are explored. The results show that the change of u* along radial direction r* shows the relation of u*~r*−2 for the neutral squirmer, and u*~r*−1 for the pusher and puller. With the increase of Re, u* of the pusher increases monotonically, but u* of the puller decreases from Re = 0.01 to 0.3, and then increases from Re = 0.3 to 3. The values of P* of the pusher and puller are the same for 0.01 ≤ Re ≤ 0.3; P* of the pusher is larger than that of the puller when Re > 0.3. η of the pusher and puller increases with increasing Re, but the pusher has a larger η than the puller at the same Re. u* and P* decrease with increasing AR, and the pusher and puller have the largest and least u*, respectively. The values of P* of the pusher and puller are almost the same and are much larger than those of the neutral squirmer. With the increase of AR, η increases for the neutral squirmer, but changes non-monotonically for the pusher and puller.

Partitive pronouns in intransitive contexts in Italian and Dutch

AbstractIn the literature it is often assumed that partitive pronouns can only be used in combination with elliptical objects of transitive or unaccusative verbs. Some counterevidence has been provided as well, however, showing that partitive pronouns may also occur with intransitive verbs. In this paper it is investigated, by means of a Grammaticality Judgment Task, if native speakers of Italian and Dutch accept the use of the partitive pronoun with three types of intransitive verbs, in combination with an elliptical quantified adverbial NP. It is shown that both groups of participants were quite ready to accept the partitive pronoun in these cases, in some contexts more than in others. Various explanations for the results are considered and one more specific suggestion is made to account for the data, also based on a comparison with other constructions and other languages.

Recognition of overlapping elliptical objects in a binary image

Recognition of overlapping objects is required in many applications in the field of computer vision. Examples include cell segmentation, bubble detection and bloodstain pattern analysis. This paper presents a method to identify overlapping objects by approximating them with ellipses. The method is intended to be applied to complex-shaped regions which are believed to be composed of one or more overlapping objects. The method has two primary steps. First, a pool of candidate ellipses are generated by applying the Euclidean distance transform on a compressed image and the pool is filtered by an overlaying method. Second, the concave points on the contour of the region of interest are extracted by polygon approximation to divide the contour into segments. Then, the optimal ellipses are selected from among the candidates by choosing a minimal subset that best fits the identified segments. We propose the use of the adjusted Rand index, commonly applied in clustering, to compare the fitting result with ground truth. Through a set of computational and optimization efficiencies, we are able to apply our approach in complex images comprised of a number of overlapped regions. Experimental results on a synthetic data set, two types of cell images and bloodstain patterns show superior accuracy and flexibility of our method in ellipse recognition, relative to other methods.

Ellipse R-CNN: Learning to Infer Elliptical Object From Clustering and Occlusion.

Images of heavily occluded objects in cluttered scenes, such as fruit clusters in trees, are hard to segment. To further retrieve the 3D size and 6D pose of each individual object in such cases, bounding boxes are not reliable from multiple views since only a little portion of the object's geometry is captured. We introduce the first CNN-based ellipse detector, called Ellipse R-CNN, to represent and infer occluded objects as ellipses. We first propose a robust and compact ellipse regression based on the Mask R-CNN architecture for elliptical object detection. Our method can infer the parameters of multiple elliptical objects even they are occluded by other neighboring objects. For better occlusion handling, we exploit refined feature regions for the regression stage, and integrate the U-Net structure for learning different occlusion patterns to compute the final detection score. The correctness of ellipse regression is validated through experiments performed on synthetic data of clustered ellipses. We further quantitatively and qualitatively demonstrate that our approach outperforms the state-of-the-art model (i.e., Mask R-CNN followed by ellipse fitting) and its three variants on both synthetic and real datasets of occluded and clustered elliptical objects.

Sustained representation of perspectival shape

Arguably the most foundational principle in perception research is that our experience of the world goes beyond the retinal image; we perceive the distal environment itself, not the proximal stimulation it causes. Shape may be the paradigm case of such "unconscious inference": When a coin is rotated in depth, we infer the circular object it truly is, discarding the perspectival ellipse projected on our eyes. But is this really the fate of such perspectival shapes? Or does a tilted coin retain an elliptical appearance even when we know it's circular? This question has generated heated debate from Locke and Hume to the present; but whereas extant arguments rely primarily on introspection, this problem is also open to empirical test. If tilted coins bear a representational similarity to elliptical objects, then a circular coin should, when rotated, impair search for a distal ellipse. Here, nine experiments demonstrate that this is so, suggesting that perspectival shapes persist in the mind far longer than traditionally assumed. Subjects saw search arrays of three-dimensional "coins," and simply had to locate a distally elliptical coin. Surprisingly, rotated circular coins slowed search for elliptical targets, even when subjects clearly knew the rotated coins were circular. This pattern arose with static and dynamic cues, couldn't be explained by strategic responding or unfamiliarity, generalized across shape classes, and occurred even with sustained viewing. Finally, these effects extended beyond artificial displays to real-world objects viewed in naturalistic, full-cue conditions. We conclude that objects have a remarkably persistent dual character: their objective shape "out there," and their perspectival shape "from here."

Image Conditions for Elliptical-Coordinate Separation-of-Variables Acoustic Multiple Scattering Models with Perfectly Reflecting Flat Boundaries: Application to in Situ Tunable Noise Barriers

SummaryTwo-dimensional time-harmonic multiple scattering problems are addressed for a finite number of elliptical objects placed in wedge-shaped acoustic domains including half-plane and right-angled corners. The method of separation of variables in conjunction with the addition theorems is employed in the elliptical coordinates. The wavefunctions are represented in terms of radial and angular Mathieu functions. The method of images is applied to consider the effect of the infinitely long flat boundaries which are perfectly reflecting: either rigid or pressure release. The wedge angle is $\pi/n$ rad with integer $n$; image ellipses must be appropriately rotated to realise the mirror reflection. Then, the ‘image conditions’ are developed to reduce the number of unknowns by expressing the unknown expansion coefficients of image scattered fields in terms of real counterparts. Use of image conditions, therefore, leads to the $4n^2$-fold reduction in the size of a matrix for direct solvers and $2n$-times faster computation in building the system of linear equations than the approach without using them. Multiple scattering models using image conditions are formulated for rigid, pressure release and fluid ellipses under either plane- or cylindrical-wave incidence, and are numerically validated by the boundary element method. Furthermore, potential applications are presented: arrays of elliptically shaped scatterers make in situ tunable noise barriers by rotating scatterers. Finally, polar-coordinate image conditions (for circular objects) are also discussed when coordinates local to circles are also rotated. In Appendix, analytic formulae are provided, which permits the elliptical-coordinate addition theorems used in this article to be calculated by summation instead of numerical integration.

On the Nonexistence of Verb-Stranding VP-Ellipsis

An increasingly popular analysis of object gap sentences in many languages derives them in two steps: (a) V-raising out of VP, and (b) VP-ellipsis of the remnant, stranding the verb (V-stranding VP-ellipsis, VSVPE). For Hebrew, Hindi, Russian, and Portuguese, I show this analysis to be inadequate. First, it undergenerates elliptical objects in various environments, and second, it overgenerates nonexisting adjunct-including readings. For all the problematic data, simple argument ellipsis provides a unified explanation. The absence of VSVPE in languages that do allow V-raising and Aux-stranding VP-ellipsis raises an intriguing problem for theories addressing the interaction of head movement and ellipsis.

Numerical modelling and comparison of the temporal evolution of mantle and tails surrounding rigid elliptical objects in simple shear regime under stick and slip boundary conditions

Structures associated with rigid inclusions are a rich source of evidence to understand the local deformation regime. The behaviour of rigid objects in modelled here as being immersed in a linear Newtonian fluid with either (i) a stick boundary condition (continuity of stress and velocity across the boundary) or (ii) a slip boundary condition (continuity of boundary normal stress and velocity across the boundary with zero shear stress at the boundary). Of particular interest are the types of structures developed in a concentric region adjacent to the object termed the mantle. A model of the displacement of points around the inclusion comprises a set of ordinary differential equations which are solved numerically. A comprehensive set of simulations for a variety of mantle sizes, object aspect ratios, initial orientations as well as different boundary conditions has been performed. A comparison between natural examples and model output indicates a level of consistency. The resulting structures differ in detail and in a broader sense. In general δ-type structures only develop when stick boundary conditions are in operation. In contrast, σ-type structures at high strain are restricted to slip boundary conditions. Slip conditions also tend to be the source of complex mantle types involving more than one generation of mantle structures or wings. Furthermore, our model indicates that using asymmetry of orientation of objects relative to the shear direction may be problematic when used alone, particularly if stick boundary conditions prevail but that together with mantle structures there is less chance of confusion.

Ellipse proposal and convolutional neural network discriminant for autonomous landing marker detection

AbstractAutonomous landing in complex environments is a critical problem for unmanned aerial vehicle autonomous control, and efficiently detecting landing identification mark in real‐world scenario is still challenging. Due to the limited computational power of airborne computing equipment, current target detection algorithms cannot meet the demand efficiently. In this paper, we proposed a new landing marker detection algorithm for autonomous landing systems in a real environment. We used an ellipse detection algorithm to detect the ellipse landmark or other elliptical objects. Furthermore, convolution neural networks were utilized to obtain the correct landmarks, which is robust, fast and can achieve a speed of 25 fps with 720p resolution video on an Intel NUC onboard computer. Unlike the other methods, the accuracy and speed of our algorithm is verified in a real‐time application with more harsh conditions. During system testing, the flight system can detect the object above 20 m, track it, and automatically land on it with this vision algorithm. The algorithm has helped us achieve the first position at Mohamed Bin Zayed International Robotics Challenge in Abu Dhabi this year.

Separating Touching Cells Using Pixel Replicated Elliptical Shape Models.

One of the most important and error-prone tasks in biological image analysis is the segmentation of touching or overlapping cells. Particularly for optical microscopy, including transmitted light and confocal fluorescence microscopy, there is often no consistent discriminative information to separate cells that touch or overlap. It is desired to partition touching foreground pixels into cells using the binary threshold image information only, and optionally incorporating gradient information. The most common approaches for segmenting touching and overlapping cells in these scenarios are based on the watershed transform. We describe a new approach called pixel replication for the task of segmenting elliptical objects that touch or overlap. Pixel replication uses the image Euclidean distance transform in combination with Gaussian mixture models to better exploit practically effective optimization for delineating objects with elliptical decision boundaries. Pixel replication improves significantly on commonly used methods based on watershed transforms, or based on fitting Gaussian mixtures directly to the thresholded image data. Pixel replication works equivalently on both 2-D and 3-D image data, and naturally combines information from multi-channel images. The accuracy of the proposed technique is measured using both the segmentation accuracy on simulated ellipse data and the tracking accuracy on validated stem cell tracking results extracted from hundreds of live-cell microscopy image sequences. Pixel replication is shown to be significantly more accurate compared with other approaches. Variance relationships are derived, allowing a more practically effective Gaussian mixture model to extract cell boundaries for data generated from the threshold image using the uniform elliptical distribution and from the distance transform image using the triangular elliptical distribution.

Novel and Efficient Approach for Automated Separation, Segmentation, and Detection of Overlapped Elliptical Red Blood Cells

Shape recognition is considered as one of the challenges in automated digital image analysis and computer vision. One of the most commonly used shapes is the ellipse which is of great importance for many industrial and biomedical applications. In this study, a novel technique is proposed for segmenting and separating of overlapped elliptical shape objects using concavity analysis and several morphological image processing techniques. A comparative study of the detection speed and accuracy of elliptical objects between Iterative Random Hough Transformation (IRHT) algorithm approach and Direct Least Squares Fitting (DLSF) of Ellipses method has shown the great superiority of DLSF in both the speed and accuracy of recognition. The validation of the proposed techniques for segmentation and detection along with calculation of the efficiency of the system has shown those techniques to be robust and effective for automation of synthetic and real elliptical shapes. The red blood cells (RBCs) microscopic images of the blood smear in Hereditary Elliptocytosis disorder is studied as real elliptical shapes and a quantitative analysis was implemented on the detected RBCs, where the distribution parameters of the ellipse size (area), Roundness, Eccentricity, and Ellipticity are estimated in addition to RBCs counting. The proposed detection approach is successful in building a fully autonomous and accurate system with ellipse analysis capabilities.

Implementing of the ISON project in Northern Mexico

Abstract ISON, being an open international project that collects and interprets data about space objects for scientific analysis and spacecraft operators, includes about 40 observational sites. An involvement of two Mexican sites participating in optical observations of geostationary and highly elliptical objects as a part of the ISON project is considered. A brief description of the facilities and their observation statistics are given. Prospects for the further development of sites for monitoring near-Earth objects in Mexico are presented, including data of astronomical observing conditions from field stations.

A Parallel Algorithm for the Counting of Ellipses Present in Conglomerates Using GPU

Detecting and counting elliptical objects are an interesting problem in digital image processing. There are real-world applications of this problem in various disciplines. Solving this problem is harder when there is occlusion among the elliptical objects, since in general these objects are considered as part of the bigger object (conglomerate). The solution to this problem focusses on the detection and segmentation of the precise number of occluded elliptical objects, while omitting all noninteresting objects. There are a variety of computational approximations that focus on this problem; however, such approximations are not accurate when there is occlusion. This paper presents an algorithm designed to solve this problem, specifically, to detect, segment, and count elliptical objects of a specific size when these are in occlusion with other objects within the conglomerate. Our algorithm deals with a time-consuming combinatorial process. To optimize the execution time of our algorithm, we implemented a parallel GPU version with CUDA-C, which experimentally improved the detection of occluded objects, as well as lowering processing times compared to the sequential version of the method. Comparative test results with another method featured in literature showed improved detection of objects in occlusion when using the proposed parallel method.

Segmentation of Overlapping Elliptical Objects Using K-Mean Clustering Method

The aim of the Segmentation of overlapping objects is to direct the issue of representation of multiple objects with partial views. In different applications, overlapping or impeded articles happen, for example, morphology analysis of atomic or cell objects in biomedical and industrial imagery in which by the size and shape of quantitative investigation of individual items is desired. We propose an algorithm specialized in ellipse detection technique using k-mean clustering to detect elliptical objects. The techniques used in this new method are very simple and intuitive. The new technique mainly consists of four steps: (1) Selecting input image; (2) detect the centre of the ellipse by using bounded erosion and fast radial symmetry called as detection of seed points (3) find the edge points on the ellipse by contour evidence detection using specialized ellipse detection technique with K-Means clustering; and (4) performing contour estimation method. The proposed work is performed using two different images which give promising results. The number of detected objects in image 1 using previous method is 26 objects and with proposed method are 16 objects. Whereas the number of detected objects in image 2 using previous method is 14 objects and with proposed method is 20 objects.

A Fast Ellipse Detector Using Projective Invariant Pruning.

Detecting elliptical objects from an image is a central task in robot navigation and industrial diagnosis, where the detection time is always a critical issue. Existing methods are hardly applicable to these real-time scenarios of limited hardware resource due to the huge number of fragment candidates (edges or arcs) for fitting ellipse equations. In this paper, we present a fast algorithm detecting ellipses with high accuracy. The algorithm leverages a newly developed projective invariant to significantly prune the undesired candidates and to pick out elliptical ones. The invariant is able to reflect the intrinsic geometry of a planar curve, giving the value of -1 on any three collinear points and +1 for any six points on an ellipse. Thus, we apply the pruning and picking by simply comparing these binary values. Moreover, the calculation of the invariant only involves the determinant of a 3×3 matrix. Extensive experiments on three challenging data sets with 648 images demonstrate that our detector runs 20%-50% faster than the state-of-the-art algorithms with the comparable or higher precision.

Signal response of wire-mesh sensors to an idealized bubbly flow

Abstract Wire-mesh sensors are widely used to characterize gas-liquid two-phase flows and single-phase mixing processes. The geometry of the electrode grids and the way of the signal readout generates a three-dimensional electrical field in the vicinity of the electrode wires. Resulting electrical currents at the receiver electrodes, representing the primary measuring information, are calculated by a three-dimensional potential field simulation within the sensitive volume formed by the electrode wires, whereas bubbles are taken into account as simplified, spherical or elliptical objects placed at different locations in the calculation domain. The response of the sensor to the passage of such synthetic bubbles is studied. A significant deviation from the linear dependency between the received current and the local instantaneous gas fraction is found. Overshoots of the current above the reference value obtained by calibration in plain liquid occur. Furthermore, the response of the sensor depends on the axial distance between the transmitter and the receiver electrode grids. Swarms of bubbles of small size passing through the grids of the wire-mesh sensor lead to an average decrease of the current which can be described by the average conductivity of an emulsion according to Maxwell.

Depletion forces on circular and elliptical obstacles induced by active matter.

Depletion forces exerted by self-propelled particles on circular and elliptical passive objects are studied using numerical simulations. We show that a bath of active particles can induce repulsive and attractive forces which are sensitive to the shape and orientation of the passive objects (either horizontal or vertical ellipses). The resultant force on the passive objects due to the active particles is studied as a function of the shape and orientation of the passive objects, magnitude of the angular noise, and distance between the passive objects. By increasing the distance between obstacles the magnitude of the repulsive depletion force increases, as long as such a distance is less than one active particle diameter. For longer distances, the magnitude of the force always decreases with increasing distance. We also found that attractive forces may arise for vertical ellipses at high enough area fraction.