scholarly journals Rotation Angle Estimation of JPEG Compressed Image by Cyclic Spectrum Analysis

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1431
Author(s):  
Shuxian Dai ◽  
Yujin Zhang ◽  
Wanqing Song ◽  
Fei Wu ◽  
Lijun Zhang
Keyword(s):  
Rotation Angle ◽  
Absolute Error ◽  
Algorithm Performance ◽  
Angle Estimation ◽  
Image Rotation ◽  
Peak Point ◽  
Shortest Distance ◽  
Peak Points ◽  
Peak Value ◽  
Cyclic Spectrum

Image rotation is a common auxiliary method of image tampering, which can make the forged image more realistic from the geometric perspective. Most algorithms of image rotation angle estimation employ the peak value on the Fourier spectrum; however, JPEG post-processing brings additional peak interferences to the spectrum, which has a great impact on algorithm performance. In this paper, angle estimation is carried out for images compressed by JPEG. Firstly, the Fourier cyclic spectrum of image covariance is calculated, followed by semi-soft threshold wavelet transform to eliminate the block artefacts brought by JPEG compression. According to the shortest distance principle in the range of the limited amplitude, the processed cyclic spectral data are sorted to select the peak points. Finally, according to the selected peak point, the corresponding position coordinates of the theoretical peak point are found, and the rotation angle of the image is estimated by the theoretical peak point. Experimental results demonstrate that the average absolute error of the proposed algorithm is significantly lower than that of the state-of-the-art methods investigated, which highlights the promising potential of the proposed method as an image resampling detector in practical forensics applications.

Local Upsampling Fourier Transform for High Accuracy Image Rotation Estimation

2011 ◽  
Vol 268-270 ◽  
pp. 1488-1493 ◽  
Author(s):  
Cai Ling Wang ◽  
Chun Xia Zhao ◽  
Jing Yu Yang
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Rotation Angle ◽  
Estimation Algorithm ◽  
High Accuracy ◽  
Angle Estimation ◽  
Image Rotation ◽  
Local Neighborhood ◽  
Robust To Noise ◽  
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.

Replacing DWT with DTCWT in blind image rotation angle estimation

2021 ◽  
Keyword(s):  
International Symposium ◽  
Fast Track ◽  
Rotation Angle ◽  
Angle Estimation ◽  
Image Rotation ◽  
Electronic Imaging ◽  
Blind Image

Fast track article for IS&T International Symposium on Electronic Imaging 2021: Media Watermarking, Security, and Forensics 2021 proceedings.

scholarly journals Sliding Mode Observer-Based Load Angle Estimation for Salient-Pole Wound Rotor Synchronous Generators

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1609 ◽  
Author(s):  
Nikola Lopac ◽  
Neven Bulic ◽  
Niksa Vrkic
Keyword(s):  
Power System ◽  
Sliding Mode ◽  
Synchronous Generator ◽  
Absolute Error ◽  
Sliding Mode Observer ◽  
Adaptive Observer ◽  
System Stability ◽  
Angle Estimation ◽  
Salient Pole ◽  
Load Angle

Synchronous generator load angle is a fundamental quantity for power system stability assessment, with possible real-time applications in protection and excitation control systems. Commonly used methods of load angle determination require additional measuring equipment, while existing research on load angle estimation for wound rotor synchronous generator has been limited to the estimator based on the generator’s phasor diagram and estimators based on artificial neural networks. In this paper, a load angle estimator for salient-pole wound rotor synchronous generator, based on a simple sliding mode observer (SMO) which utilizes field current, stator voltages, and stator currents measurements, is proposed. The conventional SMO structure is improved with use of hyperbolic tangent sigmoid functions, implementation of the second order low-pass filters accompanied with corresponding phase delay compensation, and introduction of an adaptive observer gain proportional to the measured field current value. Several case studies conducted on a generator connected to a power system suggest that the proposed estimator provides an adequate accuracy during active and reactive power disturbances during stable generator operation, outperforming the classical phasor diagram-based estimator by reducing mean squared error by up to 14.10%, mean absolute error by up to 41.55%, and maximum absolute error by up to 8.81%.

CAD-MAP and estimation of ALV positions in mountainous areas

Robotica ◽  
1994 ◽  
Vol 12 (4) ◽  
pp. 287-297 ◽  
Keyword(s):  
Computational Efficiency ◽  
Solution Method ◽  
Vision System ◽  
Position Estimation ◽  
Mountainous Area ◽  
Mountainous Areas ◽  
Land Vehicle ◽  
Peak Point ◽  
Peak Points ◽  
Solution Accuracy

SUMMARYPosition estimation is a key issue for an ALV Autonomous Land Vehicle) in navigating a mountainous area. The unevenness of the terrain makes mechanical velocity sensors inaccurate (due to wheel slippage), and the lack of appropriate landmarks complicates the problem. In this paper, we present a solution method using features of the skyline. The skyline from the vision system is assumed given, and compared with a computer map, called the CAD-MAP. The algorithm is composed of: a) Identification of the peak points in the camera skyline, b) Computing the ALV position for the identified peak points, and c) Searching for the corresponding peak point in the CAD-MAP. Heuristics for computational efficiency and solution accuracy are also included in the algorithm. To test the validity and effectiveness of the algorithm, numerous simulations were performed and analyzed.

scholarly journals Rate-of-change analysis in palaeoecology revisited: a new approach

2020 ◽  
Author(s):  
Ondřej Mottl ◽  
John-Arvid Grytnes ◽  
Alistair W.R. Seddon ◽  
Manuel J. Steinbauer ◽  
Kuber P. Bhatta ◽  
...  
Keyword(s):  
Level Density ◽  
Rate Of Change ◽  
High Rate ◽  
Type I ◽  
List Type ◽  
Compositional Change ◽  
Generalised Additive Model ◽  
Peak Point ◽  
Peak Points ◽  
Point Detection

AbstractDynamics in the rate of compositional change beyond the time of human observation are uniquely preserved in palaeoecological sequences from peat or lake sediments. Changes in sedimentation rates and sampling strategies result in an uneven distribution of time intervals within stratigraphical data, which makes assessing rates of compositional change and the detection of periods with a high rate-of-change (RoC) or ‘peak-points’ challenging. Despite these known issues and their importance, and the frequent use of RoC in palaeoecology, there has been relatively little exploration of differing approaches to quantifying RoC.Here, we introduce R-Ratepol (an easy to use R package) that provides a robust numerical technique for detecting and summarising RoC patterns in complex multivariate time-ordered stratigraphical sequences. We compare the performance of common methods of estimating RoC using simulated pollen-stratigraphical data with known patterns of compositional change and temporal resolution. In addition, we apply our new methodology to four representative European pollen sequences.Simulated data show large differences in the successful detection of known patterns in RoC peak-point detection depending on the smoothing methods and dissimilarity coefficients used, and the level density and their taxonomic richness. Building on these results, we propose a new method of binning with a moving window in combination with a generalised additive model for peak-point detection. The method shows a 22% increase in the correct detection of peak-points and 4% lower occurrence of false positives compared to the more traditional way of peak selection by individual levels, as well as achieving a reasonable compromise between type I and type II errors. The four representative pollen sequences from Europe show that our methodological combination also performs well in detecting periods of significant compositional change including the onset of human activity, early land-use transformation, and changes in fire frequency.Expanding the approach using R-Ratepol to the increasingly available stratigraphical data on pollen, chironomids, or diatoms will allow future palaeoecological and macroecological studies to quantify, and then attribute, major changes in biotic composition across broad spatial areas through time.

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