Rotation Angle Estimation Research Articles

Assessment of myocardial elastography performance in phantoms under combined physiologic motion configurations with preliminary in vivo feasibility

Myocardial elastography (ME) is a non-invasive, ultrasound-based strain imaging technique, which can detect and localize abnormalities in myocardial function. By acquiring radio-frequency (RF) frames at high frame rates, the deformation of the myocardium can be estimated, and used to identify regions of abnormal deformation indicative of cardiovascular disease. In this study, the primary objective is to evaluate the effect of torsion on the performance of ME, while the secondary objective is to image inclusions during different motion schemes. Finally, the phantom findings are validated with an in vivo human case. Phantoms of homogeneous stiffness, or containing harder inclusions, were fixed to a pump and motors, and imaged. Incremental displacements were estimated from the RF signals, and accumulated over a motion cycle, and rotation angle, radial strain and circumferential strain were estimated. Phantoms were subjected to four motion schemes: rotation, torsion, deformation, and a combination of torsion and deformation. Sonomicrometry was used as a gold standard during deformation and combined motion schemes. In the rotation scheme, the input and estimated rotation angle agree in both the homogeneous and inclusion phantoms. In the torsion scheme, the estimated rotation angle was found to be highest, closest to the source of torsion and lowest farthest from the source of torsion. In the deformation scheme, if an inclusion was not present, the estimated strain patterns accurately depicted homogeneity, while if an inclusion was present, abnormalities were observed which enabled detection of the inclusion. In addition, no significant rotation was detected. In the combined scheme, if an inclusion was not present, the estimated strain patterns accurately depicted homogeneity, while, if an inclusion was present, abnormalities were observed which enabled detection of the inclusion. Also, torsion was separated from the combined scheme and was found to be similar to the pure torsion findings. This study shows ME to be capable of accurately depicting and distinguishing between different types of motion schemes, and to be sensitive to stiffness changes in localized regions of tissue-mimicking phantoms under physiologic cardiac motion configurations, while strains estimated in the combined motion scheme were noisier than in individual motion schemes. Finally, ME was shown to be capable of distinguishing between deformation and rotation in a normal human heart in vivo.

A fast image registration approach based on SIFT key-points applied to super-resolution

An accurate image registration is a fundamental stage in many image processing problems. In this paper, a new and fast registration approach based on scale invariant feature transform (SIFT) key-points, under Euclidean transformation model, is proposed. The core idea of the proposed method is estimation of rotation angle and vertical and horizontal shifts using averaging of differences of SIFT key-point pairs locations. The method is simple but requires some tuning modules for accurate estimation. Orientation modification and compensation and shift compensation are some of the proposed modules. The proposed method is fast, about ive times faster than RANSAC method for model parameters estimation. The accuracy of the proposed method is compared with some popular registration methods. Various comparisons have been done with LIVE database images with known motion vectors. The experimental results over two real video sequences show the high performance of the proposed algorithm in a super-resolution application.

ART의 위상정보를 이용한 회전각도 추정 방법

본 논문에서는 두 영상간의 회전각도를 추정하는 방법들 중에서, 정확도에서 높은 성능을 제공하는 저니키 모멘트의 위상을 이용한 방법들의 회전각도 추정 결과의 정확도를 비교하여 제시하고, 기존의 방법들보다 정확하게 각도를 추정하는 angular radial transform(ART) 계수들의 위상성분을 이용한 회전각도 추정방법을 제안한다. 제안하는 방법은 Revaud가 제안한 저니키 모멘트를 이용한 회전각도 추정 방법[1]을 ART로 확장한 방법이다. ART는 저니키 모멘트에 비해서 회전에 의한 영상의 변화를 보다 효과적으로 서술할 수 있는 기저함수의 생성이 가능하기 때문에 저니키 모멘트보다 두 영상간의 회전각도를 정확히 추정하는 것을 가능하게 한다. MPEG-7 데이터셋을 이용한 실험 결과, 제안하는 방법이 제곱평균제곱근오차(root mean square error) 대 커버리지(coverage)를 기준으로한 성능비교에서 가장 우수한 성능을 보였다. Several methods which utilize the phase of Zernike moments (ZMs) to estimate the rotation angle have shown good performance in terms of accuracy. In this paper, we provides the performance comparison results of the existing rotation angle estimation methods based on ZMs and propose an extension of Revaud et al.'s method [1] which utilizes the phase of ZMs; the proposed method uses angular radial transform coefficients instead of ZMs and yields better performance than the ZMs based methods in terms of accuracy. A set of ART can describe angular variation of image more intensively than ZMs, it enables more accurate estimation of the rotation angle than ZMs. In the experiments, the proposed method outperforms ZMs based method. Comparisons were made in terms of the root mean square error vs. the coverage on MPEG-7 shape dataset.

Study and Realization of Large Rotation Angle Matching Images Algorithm Based on Charateristic Matching

Combining the advantages of SIFT charateristic matching and pyramid image matching, this paper aims to solve the matching problem of automatic rotation with large rotation angle in aerial photographing. To start with, match the images at the highest pyramid level with SIFT characteristic matching method. Then use the RANSAC algorithm to combine the results from SIFT method. Before matching, predict the initial location of the matching points by using the estimated rotation angle and then make rotation compensation of the matching window images. Last, validate the method by carrying out an aerial digital imagery with large rotation of a certain area.

501 フーリエ変換差分法による基板画像の欠陥検出(OS7-1 オーガナイズドセッション《精密/微細加工と評価》)

In defect detection of Printed Circuit Board(PCB) by using image processing, the displacement between two inspected images contains both parallel shift and rotation. The existing simple method, however, is not feasible due to its expesive computational cost for high resolution images. To overcome such a problem, we propose Fourier Transform Difference Method(FTDM) to calculate the shift-invariant difference between amplitudes of two input images. If the images are rotated, Rotated Ring Correlation(RRC) is used, which significantly reduces the number of repeat matching. The algorithm is implemented on MacOS X and evaluated with PCB images. Other FT-based methods such as POC and RIPOC are also implmented and compared with ours. Experimental results show that by carefully selecting calculation domains, these methods can be accelerated enough for use in factory production line, and that FTDM is supirior in precision of the rotation angle estimation.

Local Upsampling Fourier Transform for High Accuracy Image Rotation Estimation

A high accuracy rotation angle estimation algorithm based on Local Upsampling Fourier Transform (LUFT) is developed in this paper. The LUFT uses a hierarchical strategy to estimate the rotation, which consists of a transformation of rotation to translation, a fast coarse rotation estimation and a robust refinement stage as well. The coarse rotation is estimated through the conventional Phase Only Correlation (POC), then, it is refined by the resampling technique within a local neighborhood in frequency domain. Furthermore, as will be shown in many experiments, the LUFT can achieve high accuracy rotation estimation, where the accuracy is tunable to some extent. Specially, it is efficient and robust to noise.

Detecting Partial Duplications in an Image -The Improvement of Estimating Rotation Angle and Reversal-

We present a method for improving the accuracy of detecting the duplicated regions, accompanied with rotation and/or reversal, in an image. In judgment of reversal and estimation of rotation angle, we add the following processes, 1) paring pixels by principle component values, 2) calculating gradation centroid vectors for each of paired pixels, 3) evaluating the difference in angles and magnitudes between the centroid vectors. We conducted an experiment by using 100 duplicated images. The proposed method gave the correct estimation for 90 images, while the conventional one for 68 images.

On-line Rotation Invariant Estimation and Recognition

Rotation invariant estimation is an important and computationally difficult process in the real-time human computer interaction. Our new methodologies propose here for on-line image rotation angle estimation, correction and feature extractions based on line integrals. We reveal that a set of projection data of line integrals from single (fan-arc and fan-beam) or multi point sources (Radon transform) are employed for orientation estimation. After estimating orientation, image angle variations are altered to its principal direction. We further combine Boltzmann machine and k-mean clustering to obtain parameter optimized Gabor filters, which are used to extract non-redundant compact set of features for classification. The proposed method of fan-line, fan-arc and Radon transform are compared for real-time image orientation detection. Accuracy of classification is evaluated with the classifiers viz., back propagation, Hamming neural network, Euclidean-norm distance, and k-nearest neighbors. Experiment on a database of 535 images consisting of license plate and iris images. The viability of suggested algorithms has been tested with different classifiers. Thus, this paper proposes an efficient rotation invariant recognition for on-line images recognition.

Diffusion Tensors for Processing Sheared and Rotated Rectangles

Image restoration and simplification methods that respect important features such as edges play a fundamental role in digital image processing. However, known edge-preserving methods like common nonlinear diffusion methods tend to round vertices for large diffusion times. In this paper, we adapt the diffusion tensor for anisotropic diffusion to avoid this effects in images containing rotated and sheared rectangles, respectively. In this context, we propose a new method for estimating rotation angles and shear parameters based on the so-called structure tensor. Further, we show how the knowledge of appropriate diffusion tensors can be used in variational models. Numerical examples including orientation estimation, denoising and segmentation demonstrate the good performance of our methods.

Improving Zernike Moments Comparison for Optimal Similarity and Rotation Angle Retrieval

Zernike moments constitute a powerful shape descriptor in terms of robustness and description capability. However the classical way of comparing two Zernike descriptors only takes into account the magnitude of the moments and loses the phase information. The novelty of our approach is to take advantage of the phase information in the comparison process while still preserving the invariance to rotation. This new Zernike comparator provides a more accurate similarity measure together with the optimal rotation angle between the patterns, while keeping the same complexity as the classical approach. This angle information is particularly of interest for many applications, including 3D scene understanding through images. Experiments demonstrate that our comparator outperforms the classical one in terms of similarity measure. In particular the robustness of the retrieval against noise and geometric deformation is greatly improved. Moreover, the rotation angle estimation is also more accurate than state-of-the-art algorithms.

Entanglement, Nonlinear Dynamics, and the Heisenberg Limit

We show that quantum Fisher information provides a sufficient condition to recognize multiparticle entanglement in an N qubit state. The same criterion gives a necessary and sufficient condition for sub-shot-noise phase sensitivity in the estimation of a collective rotation angle theta. The analysis therefore singles out the class of entangled states which are useful to overcome classical phase sensitivity in metrology and sensors. We finally study the creation of useful entangled states by the nonlinear dynamical evolution of two decoupled Bose-Einstein condensates or trapped ions.

ディジタル画像内での部分複写の検出

We propose a method for detecting the duplicated regions in a digital image. Conventional methods treat only a simple case of translation duplication, whereas we treat a complex duplication accompanied with rotation and/or reversal. The proposed method features rotation invariant image features that can be used to estimate rotation angle and judge whether reversal exists (OK?). We can transform an input image by estimating the rotation angle and/or reversal. In an extended image combining the input and transformed images, pixels with similar features are searched to determine the duplicated location. Experimental results show the effectiveness of the proposed method.

Evaluation of polarization angle rotation of propagating light in a partially ionized atmosphere under discharge conditions

AbstractThe polarization angle rotation of the propagating beam was estimated in a partially ionized atmosphere under discharge conditions. The polarization plane angle rotation is caused by the magneto‐optical effect (Faraday effect). The estimated rotation angle is of the order of <1 degree, but can be detected with an extinction ratio of polarization of >30 dB. We examined the effects of the optical path length of repeating square mirror optics and an air‐gap length of the discharge on the rotation angle. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 163(4): 1–7, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20689

A Novel Registration Method for Interval Change Detection between Two Chest X-ray Images With Different Rotation Angles

Registration is an important process to detect interval changes between two chest x-ray images. However, the conventional registration methods suffer from misregistration because of the difference in rotation angles of human body around an axis parallel to the x-ray films, such as anteroposterior inclination. Such difference causes permutation of the shadows between the two images, which makes registration difficult. This article proposes a novel registration method in cases where two chest x-ray images have different rotation angles. Twelve x-ray images taken from a chest phantom and four chest photofluorograms of two patients were used to evaluate the performance. First, the proposed algorithm estimates the rotation angles of the body from the pair of two x-ray images based on the function describing the relationship between a point in the current image and that in the previous image, which is derived from a three-dimensional rotational model of the body. Then it aligns two images according to the function. From the results of estimating rotation angles, it was found that proposed method can estimate the angles with an error of less than 1 degrees. Then two physicians evaluated the subtraction images and confirmed that this approach makes it possible to detect the interval changes accurately even if there are permutations of shadows in the x-ray image. The proposed method is superior to the conventional one when two chest x-ray images have different rotation angles.

Theory and Experiments of Angular Vertical Comb-Drive Actuators for Scanning Micromirrors

We report on the theory and experiments of scanning micromirrors with angular vertical comb-drive (AVC) actuators. Parametric analyses of rotational vertical comb-drive actuators using a hybrid model that combines two-dimensional finite-element solutions with analytic formulations are described. The model is applied to both AVC and staggered vertical comb-drive (SVC) actuators. Detailed design tradeoffs and conditions for pull-in-free operations are discussed. Our simulation results show that the fringe fields play an important role in the estimation of maximum continuous rotation angles, particularly for combs with thin fingers, and that the maximum scan angle of the AVC is up to 60% larger than that of the SVC. Experimentally, a large dc continuous scan angle of 28.8/spl deg/ (optical) has been achieved with a moderate voltage (65 V) for a 1-mm-diameter scanning micromirror with AVC actuators. Excellent agreement between the experimental data and the theoretical simulations has been obtained.

Estimation of rotation and slant angles of a textured plane using spectral moments

AbstractThis paper proposes a method for estimating rotation and slant angles with slant direction of a textured plane using spectral moments. When a textured plane rotates and slants, the 2D power spectrum also rotates and expands toward the slant direction. Thus, the spectral moments also change corresponding to the rotation and expansion. The rotation angle, slant angle, and slant direction of a textured plane can be derived from the comparison between the second‐order spectral moments of a standard image and those of a test image. We show the validity of the method in simulations using the synthesized images and in experiments using real images taken with a CCD camera. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(6): 21–31, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10314

Estimation of the respiratory frequency using spatial information in the VCG

A new method for extracting respiratory signals from the ECG/VCG is presented. The method is based on the alignment of an observed VCG loop to a reference loop with respect to the transformations of rotation and time synchronisation. The resulting series of estimated rotation angles reflects respiratory-induced changes in the electrical axis of the heart. The respiratory frequency is estimated by power spectral analysis of the derived respiration signal. The value of respiratory modulation of the heart rate is considered by analysing the cross power spectrum of the signals related to rotation angles and heart rate. For comparison, a respiratory signal derived from the QRS area of two different leads is implemented. The performance of the methods is validated on a database with simultaneously recorded VCG and respiratory signals acquired from 20 healthy subjects. The agreement between the respiratory frequencies obtained from the derived and the respiratory signals is presented. The angle-based respiratory signal is found to produce the best agreement with a gross median error of only 4.2%.

ニューラルネットワークによる回転パターンの認識と回転角度の推定

ニューラルネットワークによる回転パターンの認識と回転角度の推定

Faraday rotation of optically pumped sodium vapour in a weak magnetic field

Faraday rotation of optically pumped sodium atoms in a weak magnetic field, which is lower than the critical field of hyperfine splitting, was obtained theoretically. The estimated rotation angles were compared with the experiments for various magnetic fields. The measured values showed good agreement with the values calculated from the theory.

カルマン・フィルタを用いたねじり軸共振系の位置決め制御

In a magnetic tape unit, high speed and precise positioning control should be achieved. This paper demonstrates that a Kalman filter can precisely estimate the state variables for the capstan motor, combined with its torsion resonance characteristics modeling, and widen the loop bandwidth by the feedback from estimated state variables.The capstan motor is modeled as a two freedom resonant system that consists of two parts, a torque generator part and a capstan part. The Kalman filter is constructed to estimate rotation angle and rotation angle velocity for the two parts, from the motor driving current and the capstan rotation angle.The comparison between experimental frequency response for estimated state variables and calculated values confirmed that the two freedom model for the capstan motor was able to describe its actual resonant characteristics and that the Kalman filter circuit operated up to several kHz beyond the first resonant frequency for the system. The actual capstan motor was controlled by feedback from these estimated signals, based on the optimal control theory. The result shows that the loop bandwidth for the positioning control was extended about twice as wide as the conventional method, where a tachogenerator and band reject filters were used. The motor was started up for about 0.4ms.