Angle Images Research Articles

Аналоги теоремы Гаусса-Александрова для однородных ориентируемых невыпуклых многогранников с выпуклыми гранями

The paper defines the spherical image of a polyhedral angle of a uniform oriented nonconvex polyhedron, introduces the concept of curvature of realization of such an angle and proves the theorem about the equality of the area of the spherical image of a polyhedral angle with the feature ”fold” to its realization curvature.

CNN-Based Classification for Point Cloud Object With Bearing Angle Image

Convolutional neural network (CNN), one of the branches of deep neural networks, has been widely used in image recognition, natural language processing, and other related fields with great success recently. This paper proposes a novel framework with CNN to classify objects in a point cloud captured by LiDAR on urban streets. The proposed BA-CNN algorithm is composed of five steps: (i) removing ground points, (ii) clustering objects, (iii) transforming to bearing angle images, (iv) ROI selection, and (V) identifying objects by CNN. In the first step, ground points are removed by the multi-threshold-based ground detection to reduce the processing time. Then, a flood-fill-based clustering method is used for object segmentation. Those individual point cloud objects are converted to bearing angle (BA) images. Then, a well-trained CNN is used to classify objects with BA images. The main contribution of this paper is proposing an efficient recognition method that uses the information from point clouds only. In contrast, because most 3D object classifiers use the fusion of point clouds and color images, their models are very complicated and take a colossal amount of memory to store the parameters. Since the ground point detection and object clustering process all points along with the scanline-major order and layer-major order, the proposed algorithm performs better in terms of time consumption and memory consumption. In the experiment, three scenes from KITTI dataset are used for training and testing the proposed BA-CNN classifier, and the proposed BA-CNN achieves high classification accuracy.

Source depth discrimination using peak migration line of cross-correlation output in shallow water having negative thermocline

In this paper, the peak migration line of cross-correlation output is utilized to discriminate the depth of an underwater acoustic source in shallow water environment with a negative thermocline through studying the modal arrival structure of the source at different depths. The discrimination can be done according to the position of the migration line when the cross-correlation delay is zero since the type of dominant normal mode is determined by the depth of the source. Firstly, using the beam output of a vertical linear array and the received signal of a single array element to do cross-correlation processing, a two-dimensional intensity image of cross-correlation delay versus elevation angle is obtained. Then, the peaks in the angle domain at different delays can be extracted from the image. The cross-correlation peak migration line can be achieved by piecewise linear fitting which is divided into two parts corresponding to the delay being less than or equal to zero and the delay being more than zero, respectively. Finally, the source depth is determined by the position of the curve where the cross-correlation time delay is zero. Theoretical analysis shows that the migration line is little influenced by the sound velocity profile (SVP) varying with depth, the discrimination threshold is determined by the lower-order normal modes, the identification region is determined by the thickness and depth of the thermocline and the higher strength of the thermocline is instrumental in distinguishing. The numerical results and the experimental results prove the method's effectiveness which can be implemented without SVP details or mode separation, or source movement.

Impacts of CMEs on Earth Based on Logistic Regression and Recommendation Algorithm

Coronal mass ejections (CMEs) are one of the major disturbance sources of space weather. Therefore, it is of great significance to determine whether CMEs will reach the earth. Utilizing the method of logistic regression, we first calculate and analyze the correlation coefficients of the characteristic parameters of CMEs. These parameters include central position angle, angular width, and linear velocity, which are derived from the Large Angle and Spectrometric Coronagraph (LASCO) images. We have developed a logistic regression model to predict whether a CME will reach the earth, and the model yields an F1 score of 30% and a recall of 53%. Besides, for each CME, we use the recommendation algorithm to single out the most similar historical event, which can be a reference to forecast CMEs geoeffectiveness forecasting and for comparative analysis.

Complex B1+ mapping with Carr-Purcell spin echoes and its application to electrical properties tomography.

PurposeTo present a new complex‐valued B1 + mapping method for electrical properties tomography using Carr‐Purcell spin echoes.MethodsA Carr‐Purcell (CP) echo train generates pronounced flip‐angle dependent oscillations that can be used to estimate the magnitude of B1 +. To this end, a dictionary is used that takes into account the slice profile as well as T2 relaxation along the echo train. For validation, the retrieved B1 + map is compared with the actual flip angle imaging (AFI) method in a phantom (79 ε0, 0.34 S/m). Moreover, the phase of the first echo reflects the transceive phase. Overall, the CP echo train yields an estimate of the complex‐valued B1 +, allowing electrical properties tomography with both permittivity and conductivity. The presented method is evaluated in phantom scans as well as for in vivo brain at 3 T.ResultsIn the phantom, the obtained magnitude B1 + maps retrieved from the CP echo train and the AFI method show excellent agreement, and both the reconstructed estimated permittivity (79 ± 3) ε0 and conductivity (0.35 ± 0.04) S/m values are in accordance with expectations. In the brain, the obtained electrical properties are also close to expectations. In addition to the retrieved complex B1 + information, the decay of the CP echo trains also yields an estimate for T2.ConclusionThe CP sequence can be used to simultaneously provide both B1 + magnitude and phase estimations, and therefore allows for full reconstruction of the electrical properties.

Towards window state detection using image processing in residential and office building facades

Although building energy simulation is an essential tool for designers, numerous studies have proven the existence of a performance gap between the estimated and measured energy use. In response, researchers are exploring ways to collect authentic behavioural data to improve existing inaccurate data-driven occupancy behaviour models. An important occupant behaviour currently being studied is window operation behaviour as it results in large consequences on heating/cooling loads and ventilation rates of a building. Ex-situ camera-based window operation monitoring has been proposed as a solution. This study used image processing technologies that automatically identified windows on a façade and determined their individual state (i.e. open, partially open, or closed). The algorithm developed through this study yielded an 89% accuracy rate over all the windows tested. This algorithm was developed to specifically target punched façades with awning windows. Factors that affected the accuracy of ex-situ camera-based window operation monitoring included environmental conditions such as lighting, obstructions, and reflections. Furthermore, there were challenges in determining threshold values used to isolate important image data that defined the window state and location and identifying the significant peaks for window angle image data. The next steps for this research should determine appropriate threshold values that can be used universally through additional testing and to explore new image processing techniques for other window types.

Three-dimensional catheter navigation of airways using continuous-sweep limited angle fluoroscopy on a C-arm.

Purpose: To develop an imaging-based 3D catheter navigation system for transbronchial procedures including biopsy and tumor ablation using a single-plane C-arm x-ray system. The proposed system provides time-resolved catheter shape and position as well as motion compensated 3D airway roadmaps. Approach: A continuous-sweep limited angle (CLA) imaging mode where the C-arm continuously rotates back and forth within a limited angular range while acquiring x-ray images was used for device tracking. The catheter reconstruction was performed using a sliding window of the most recent x-ray images, which captures information on device shape and position versus time. The catheter was reconstructed using a model-based approach and was displayed together with the 3D airway roadmap extracted from a pre-navigational cone-beam CT (CBCT). The roadmap was updated in regular intervals using deformable registration to tomosynthesis reconstructions based on the CLA images. The approach was evaluated in a porcine study (three animals) and compared to a gold standard CBCT reconstruction of the device. Results: The average 3D root mean squared distance between CLA and CBCT reconstruction of the catheter centerline was for a stationary catheter and for a catheter moving at . The average tip localization error was and , respectively. Conclusions: The results indicate catheter navigation based on the proposed single plane C-arm imaging technique is feasible with reconstruction errors similar to the diameter of a typical ablation catheter.

Highly efficient and stable P3CT-Na based MAPbI3 solar cells with a Sn-rich ITO anode

Transmittance spectra, atomic-force microscopic images, energy-dispersive X-ray spectra and droplet contact angle images show that a facile wet etching process can be used to manipulate the thickness, surface roughness, surface chemical composition and surface wettability of the indium-tin oxide (ITO) thin films, which influences the molecular packing structure of the P3CT-Na thin films and thereby dominating the crystal quality of the CH3NH3PbI3 (MAPbI3) thin films. The power conversion efficiency (PCE) of the P3CT-Na based MAPbI3 solar cells can be improved from 17.02% to 19.35% by increasing the Sn/In concentration ratio of the ITO thin films from 0.36 to 0.47 with a facile wet etching process at a constant temperature of 40 °C. It is noted that the PCE of the optimal solar cell decreases slowly toward a stable PCE of 16% for more than 60 days under moderate environment conditions (55 ± 10 RH%).

Corn Flour Quality Identification System Based on Angle Image

Corn can be processed into corn flour, this can make it easier for consumers to consume and process it into other food ingredients. Therefore we need a system that is able to identify the quality of corn flour automatically. Data retrieval is done by inserting corn flour into a container to calculate the angle of repose. The valve of the container is opened and the cornstarch flows into a mound above the cross-sectional base. The image of the corn flour mound was taken using a cellphone camera and stored in a laptop as a database. The sample of this research is corn flour with three types of particle sizes, namely 20 mesh, 10 mesh and 8 mesh. In the identification process, the corn flour image is converted into a grayscale and binary image and cropping is done, then identified based on the calculation of the angle of repose. The results of this study obtained that the average value of 20 mesh, 10 mesh and 8 mesh corn flour was 30.91 degrees; 33.96 degrees and 36.80 degrees. After testing and comparison, it can be concluded that corn flour with good quality is corn flour with an angle of less than 32 degrees.Jagung dapat diolah menjadi tepung jagung, hal ini dapat memudahkan konsumen dalam mengonsumsi dan mengolahnya menjadi bahan pangan lain. Oleh karena itu dibutuhkan sistem yang mampu mengidentifikasi kualitas tepung jagung secara otomatis. Pengambilan data dilakukan dengan memasukkan tepung jagung ke dalam wadah hitung sudut diam. Katup wadah dibuka dan tepung jagung mengalir membentuk gundukan di atas alas penampang. Citra dari gundukan tepung jagung diambil menggunakan kamera handphone dan disimpan ke dalam laptop sebagai database. Sampel penelitian ini tepung jagung dengan tiga jenis ukuran partikel, yaitu 20 mesh, 10 mesh dan 8 mesh. Dalam proses identifikasi citra terpung jagung dikonversikan menjadi citra greyscale dan biner serta dilakukan cropping, lalu diidentifikasi berdasarkan perhitungan sudut diam. Hasil penelitian yang dilakukan mendapatkan nilai rata-rata tepung jagung 20 mesh, 10 mesh dan 8 mesh berturut-turut adalah 30,91 derajat; 33,96 derajat dan 36,80derajat. Setelah dilakukan pengujian dan perbandingan, dapat disimpulkan bahwa tepung jagung dengan kualitas baik yaitu tepung jagung dengan sudut kurang dari sama dengan 32derajat.

Real-Time Automated Classification of Sky Conditions Using Deep Learning and Edge Computing

The radiometric quality of remotely sensed imagery is crucial for precision agriculture applications because estimations of plant health rely on the underlying quality. Sky conditions, and specifically shadowing from clouds, are critical determinants in the quality of images that can be obtained from low-altitude sensing platforms. In this work, we first compare common deep learning approaches to classify sky conditions with regard to cloud shadows in agricultural fields using a visible spectrum camera. We then develop an artificial-intelligence-based edge computing system to fully automate the classification process. Training data consisting of 100 oblique angle images of the sky were provided to a convolutional neural network and two deep residual neural networks (ResNet18 and ResNet34) to facilitate learning two classes, namely (1) good image quality expected, and (2) degraded image quality expected. The expectation of quality stemmed from the sky condition (i.e., density, coverage, and thickness of clouds) present at the time of the image capture. These networks were tested using a set of 13,000 images. Our results demonstrated that ResNet18 and ResNet34 classifiers produced better classification accuracy when compared to a convolutional neural network classifier. The best overall accuracy was obtained by ResNet34, which was 92% accurate, with a Kappa statistic of 0.77. These results demonstrate a low-cost solution to quality control for future autonomous farming systems that will operate without human intervention and supervision.

Agreement Analysis on Angle Characteristics With Automated Gonioscopy.

Automated gonioscopy is a recent method of recording angle pictures. Our study shows that agreement between observers is moderate in most categories used in clinical practice, underlying its clinical usefulness but also room for improvement. Iridocorneal angle (ICA) imaging methods have been recently developed to record gonioscopic images. The purpose of this study was to perform an interrater agreement analysis of ICA photographs. Multicentric cross-sectional observational study. Consecutive patients in 2 ophthalmology departments underwent automated gonioscopy. One picture per quadrant from each eye was selected for randomization. Pictures were graded and analyzed by 4 masked glaucoma specialists regarding angle opening, width, Shaffer and Spaeth gradings and other findings. Fleiss' κ statistics was performed to assess interrater agreement. A total of 50 patients were recruited, with the sample containing a variety of diagnosis including pseudoexfoliation (22%), angle-closure suspect (12%), and pigmentary glaucoma (4%). The sample included phakic (68%) and pseudophakic patients, as well as cases with gonio-implanted surgical devices (10%). There was moderate agreement on angle opening, angle width, presence of angle vessels, and peripheral anterior synechiae (κ=0.435, 0.511, 0.558, 0.488, respectively; P<0.01). Fair agreement was observed regarding Shaffer grading, site of iris root insertion, angle pigmentation features, and the presence of iris processes. Expectedly from a 2-dimensional picture, the configuration of peripheral iris was found to have a poor agreement. Subset analysis on higher quality pictures seemed to improve agreement on pigment but did not further improve on the overall good agreement on angle opening status. Our study shows that automated gonioscopy provides moderate agreement on most clinically relevant features. Binary characteristics such as angle opening or PAS seem to be more robust than more complex angle classification parameters.

Axion-plasmon or magnetized plasma effect on an observable shadow and gravitational lensing of a Schwarzschild black hole

In this paper, we study the influence of the axion-plasmon, as proposed in (Phys. Rev. Lett. 120, 181803 (2018)) on the optical properties of the Schwarzschild black hole. Our aim is to provide a test to detect the effects of a fixed axion background using black holes. To accomplish our goal, we explore the effect of the axion-plasmon coupling on the motion of photons around the Schwarzschild black hole and check the possibility of observing those effects upon the black hole shadow, the gravitational deflection angle, Einstein rings and shadow images obtained by radially infalling gas on a black hole within a plasma medium. We find that these quantities are indeed affected by the axion-plasmon coupling parameters which consequently generalize some of the well-known results in the literature. It is shown that the size of the black hole shadow decreases with increasing axion-plasmon if observed from sufficiently large distance.

Various Methods of Image Mosaicing

Image Mosaicing is that the method of mixing 2 or additional pictures of identical scene into one image and generate panorama of high-resolution image. In this paper, we've represented the essential strategies used to generate panorama image. Our aim is to supply different strategies and algorithms used to generate wide angle image. This paper is principally for those who want to try to learn and implement image mosaicing.

Vectorial Compound Metapixels for Arbitrary Nonorthogonal Polarization Steganography

Malus' law regulating the intensity of light when passed through a polarizer, forms the solid basis for image steganography based on orthogonal polarizations of light to convey hidden information without adverse perceptions, which underpins important practices in information encryptions, anti-counterfeitings, and security labels. Unfortunately, the restriction to orthogonal states being taken for granted in the common perceptions fails to advance cryptoinformation to upgraded levels of security. By introducing a vectorial compound metapixel design, arbitrary nonorthogonal polarization multiplexing of independent grayscale images with high fidelity and strong concealment is demonstrated. The Jones matrix treatment of compound metapixels consisting of double atoms with tailored in-plane orientation sum and difference allows point-by-point configuring of both the amplitude and polarization rotations of the output beam in an analytical and linear form. With this, both multiplexing two continuous grayscale images in arbitrary nonorthogonal polarization angles and concealing grayscale image on another in an arbitrary disclosure angle window are experimentally demonstrated in the visible TiO2 metasurface platform. The methods shed new light on multifarious metaoptics by harnessing the new degree of freedom and unlock the full potential of metasurface polarization optics.

P‐12.7: An optical compensation method of Dual cell Technology

A 23.8” FHD LCD with super higher contrast ratio of 300000:1 has been developed by using a newly‐designed dual cell structure both with the same resolution and an optical compensation algorithm, it improves the contrast ratio into million levels as well as optimizes the moiré, uniformity of the viewing angle and ghost image. Based on the super higher contrast ratio, good and uniform image performance, it has been applied to the advanced medical diagnostic products.

Estimating the volume of frozen water droplets on a cold surface during the phase change with thermal image processing

In this paper, a new technique to estimate a frozen water droplet’s volume on a cold solid surface is presented, based on the contact angle and thermal images. The factors that can vary the contact angle, such as the temperature, surface roughness, and droplet size, are considered in the study. This technique can detect and obtain the volume of a single or a group of frozen droplets as soon as they are directly deposited on a cold hydrophilic surface and during the phase change from water to ice. The contact angle is pre-estimated, and the equivalent diameter is extracted from droplet's thermal image using image processing. From information on the contact angle and diameter of the deposited frozen droplet, the volume of the frozen droplet can be predicted. The evaluations show there is an average overestimation in droplets’ volumes of about 19%.

A Fast Correction Algorithm for Inverse Longitude and Latitude Mapping of Fish Eye Image

In order to solve the problem of large barrel distortion in fisheye lens, an image distortion correction algorithm based on double longitude is proposed to improve the visual effect. Firstly, in the case of unknown lens angle and non-circular fisheye image, the spherical center and its radius are obtained by using fisheye image features, and the radius is optimized to reduce pole distortion; on this basis, the fisheye image is mapped to the spherical surface by orthogonal projection strategy using double longitude model method, which is transformed into the transverse longitude and longitudinal longitude coordinates of the sphere The projection is a square plane image based on the horizontal and vertical double longitude coordinates to realize the fast and accurate image transformation.

32‐Channel self‐grounded bow‐tie transceiver array for cardiac MR at 7.0T

Design, implementation, evaluation, and application of a 32-channel Self-Grounded Bow-Tie (SGBT) transceiver array for cardiac MR (CMR) at 7.0T. The array consists of 32 compact SGBT building blocks. Transmission field ( ) shimming and radiofrequency safety assessment were performed with numerical simulations and benchmarked against phantom experiments. In vivo efficiency mapping was conducted with actual flip angle imaging. The array's applicability for accelerated high spatial resolution 2D FLASH CINE imaging of the heart was examined in a volunteer study (n=7). shimming provided a uniform field distribution suitable for female and male subjects. Phantom studies demonstrated an excellent agreement between simulated and measured efficiency maps (7% mean difference). The SGBT array afforded a spatial resolution of (0.8 × 0.8 × 2.5)mm3 for 2D CINE FLASH which is by a factor of 12 superior to standardized cardiovascular MR (CMR) protocols. The density of the SGBT array supports 1D acceleration of up to R=4 (meansignal-to-noise ratio (whole heart)≥16.7, meancontrast-to-noise ratio≥13.5) without impairing image quality significantly. The compact SGBT building block facilitates a modular high-density array that supports accelerated and high spatial resolution CMR at 7.0T. The array provides a technological basis for future clinical assessment of parallel transmission techniques.

Optimized gradient spoiling of UTE VFA-AFI sequences for robust T1 estimation with B1-field correction

Quantifying T1 relaxation times is a challenge because inhomogeneities of the B1 field have to be corrected to obtain proper values. It is a particular challenge in tissues with short T2⁎ values, for which conventional MRI techniques do not provide sufficient signal. Recently, a B1-field correction technique called AFI (Actual Flip angle Imaging) has been introduced that can be combined with UTE (ultra-short echo-time) sequences, which have much shorter echo times compared to conventional MRI techniques, allowing quantification of signal in short T2⁎ tissues. A disadvantage of AFI is that it requires very long relaxation delays between repetitions to minimize the influence of imperfect spoiling of transverse magnetization on signal behavior. In this work, we propose a novel spoiling scheme for the AFI sequence that efficiently provides accurate B1 correction maps with strongly reduced acquisition time. We validated the method with both phantom and preliminary in vivo results.

Optical schemes of super-angular AOTF-based imagers and system response analysis

We propose a super-angular aperture scheme instead of the circular aperture scheme for AOTF spectral imager to increase radiation flux of acousto-optic tunable filter (AOTF). At the same time, we quantitatively calculate the radiation flux variation caused by the super angular aperture scheme and the AOTF element response at oblique incidence. We analyze the system response of the two optical schemes and verify the simulation results through the system frequency response to compare the two AOTF optical schemes, where one is more suitable for super aperture angle imaging. We believe that the collimated optical path is more suitable for the super-angular aperture scheme because its spectral bandwidth is better than that of confocal optical scheme, and the center wavelength shift can be corrected by model or calibration.