Literatura académica sobre el tema "Mellin and scale transform"

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Artículos de revistas sobre el tema "Mellin and scale transform"

1

Pivarčiová, Elena, Daynier Rolando Delgado Sobrino, Yury Rafailovich Nikitin, Radovan Holubek, and Roman Ružarovský. "Measuring and evaluating the differences of compared images for a correct car silhouette categorization using integral transforms." Measurement Science Review 18, no. 4 (2018): 168–74. http://dx.doi.org/10.1515/msr-2018-0024.

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Abstract The present paper focuses on the analysis of the possibilities of using integral transforms for measuring and evaluating the differences of compared images (car silhouettes) with the purpose of a correct car body categorization. Approaches such as the light intensities frequency change, the application of discrete integral transforms without the use of further supplementary information enabling automated data processing using the Fourier-Mellin transforms are used within this work. The calculation of the several metrics was verified through different combinations that implied using and not using the Hamming window and a low-pass filter. The paper introduced a method for measuring and evaluating the differences in the compared images (car silhouettes). The proposed method relies on the fact that the integral transforms have their own transformants in the case of translation, scaling and rotation, in the frequency area. Besides, the Fourier-Mellin transform was to offer image transformation that is resistant to the translation, rotation and scale.
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2

Xu, Qingwen, Haofei Kuang, Laurent Kneip, and Sören Schwertfeger. "Rethinking the Fourier-Mellin Transform: Multiple Depths in the Camera’s View." Remote Sensing 13, no. 5 (2021): 1000. http://dx.doi.org/10.3390/rs13051000.

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Remote sensing and robotics often rely on visual odometry (VO) for localization. Many standard approaches for VO use feature detection. However, these methods will meet challenges if the environments are feature-deprived or highly repetitive. Fourier-Mellin Transform (FMT) is an alternative VO approach that has been shown to show superior performance in these scenarios and is often used in remote sensing. One limitation of FMT is that it requires an environment that is equidistant to the camera, i.e., single-depth. To extend the applications of FMT to multi-depth environments, this paper presents the extended Fourier-Mellin Transform (eFMT), which maintains the advantages of FMT with respect to feature-deprived scenarios. To show the robustness and accuracy of eFMT, we implement an eFMT-based visual odometry framework and test it in toy examples and a large-scale drone dataset. All these experiments are performed on data collected in challenging scenarios, such as, trees, wooden boards and featureless roofs. The results show that eFMT performs better than FMT in the multi-depth settings. Moreover, eFMT also outperforms state-of-the-art VO algorithms, such as ORB-SLAM3, SVO and DSO, in our experiments.
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3

Wang, Baocheng, Dandan Qu, Qing Tian, and Liping Pang. "Mellin Transform-Based Correction Method for Linear Scale Inconsistency of Intrusion Events Identification in OFPS." Photonic Sensors 8, no. 3 (2018): 220–27. http://dx.doi.org/10.1007/s13320-018-0486-9.

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4

VYAS, VIBHA S., and PRITI P. REGE. "GEOMETRIC TRANSFORM INVARIANT TEXTURE ANALYSIS WITH MODIFIED CHEBYSHEV MOMENTS BASED ALGORITHM." International Journal of Image and Graphics 09, no. 04 (2009): 559–74. http://dx.doi.org/10.1142/s0219467809003587.

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Texture based Geometric invariance, which comprises of rotation scale and translation (RST) invariant is finding application in various areas including industrial inspection, estimation of object range and orientation, shape analysis, satellite imaging, and medical diagnosis. Moments based techniques, apart from being computationally simple as compared to other RST invariant texture operators, are also robust in presence of noise. Zernike moments (ZM) based techniques are one of the well-established methods used for texture identification. As ZM are continuous moments, when discretization is done for implementation, errors are introduced. Error, calculated as difference between theoretically computed values and simulated values is proved to be prominent for fine textures. Therefore, a novel approach to detect RST invariant textures present in image is presented in this paper. This approach calculates discrete Chebyshev moments (CM) of log-polar transformed images to achieve rotation and scale invariance. The image is made translation invariant by shifting it to its centroid. The data is collected as samples from Brodatz and Vistex data sets. Zernike moments and its modifications, along with proposed scheme are applied to the same and Performance evaluation apart from RST invariance is noise sensitivity and redundancy. The performance is also compared with circular Mellin Feature extractors.
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5

Monakov, A. A. "An Algorithm for Estimating the Velocity of a Moving Target Based on Mellin Matched Filter." Journal of the Russian Universities. Radioelectronics 25, no. 3 (2022): 22–38. http://dx.doi.org/10.32603/1993-8985-2022-25-3-22-38.

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Introduction. Construction of the radar image of a moving target and estimation of its velocity in synthetic aperture radars (SAR) presents a relevant research problem. The low quality of radar imaging is frequently related to the phenomenon of range cell migration (RCM). Conventional methods for RCM compensation, which are successfully used to obtain radar images of stationary targets, fail to provide the required quality when applied to moving targets. At present, a number of algorithms are used to solve this problem. However, the majority of them employ optimization procedures when searching for estimates of unknown parameters, which fact greatly complicates their implementation. An exception is the LvD algorithm, which implements double keystone transform to construct a radar image without using complex estimate search procedures. Radar images are constructed in the coordinates "longitudinal velocity - lateral velocity", which facilitates estimation of the target velocity components.Aim. Development of an alternative algorithm based on the Mellin matched filter (MMF) for estimating the velocity and constructing the radar image of a moving target in a side-looking SAR.Materials and methods. The derived algorithm is based on the invariance of the integral Mellin transform to the signal scale and uses the MMF to estimate the target velocity components.Results. An algorithm for constructing the radar image of a moving target based on the MMF was synthesized. An analysis of the LvD algorithm showed its capacity for selecting the optimum scale factor when implementing a second KT. The conducted computer simulation of the MMF and LvD algorithms showed their equal accuracy. Under the same simulation scenarios, both algorithms yield effective estimates of the velocity components of a moving target when the signal-to-noise ratio is greater than -10 dB.Conclusion. The proposed algorithm for constructing a radar image can be used in SAR systems designed for detection and velocity estimation of a moving target.
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6

Chen, Hui-Chi. "Improved performance of scale-invariant pattern recognition using a combined Mellin radial harmonic function and wavelet transform." Optical Engineering 46, no. 10 (2007): 107204. http://dx.doi.org/10.1117/1.2799534.

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7

Monjur, Mehjabin Sultana, Shih Tseng, Renu Tripathi, and M. S. Shahriar. "Incorporation of polar Mellin transform in a hybrid optoelectronic correlator for scale and rotation invariant target recognition." Journal of the Optical Society of America A 31, no. 6 (2014): 1259. http://dx.doi.org/10.1364/josaa.31.001259.

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8

Lizzi, Fedele, Mattia Manfredonia та Flavio Mercati. "Localizability in κ-Minkowski spacetime". International Journal of Geometric Methods in Modern Physics 17, supp01 (2020): 2040010. http://dx.doi.org/10.1142/s0219887820400101.

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Using the methods of ordinary quantum mechanics, we study [Formula: see text]-Minkowski space as a quantum space described by noncommuting self-adjoint operators, following and enlarging T. Poulain and J.-C. Wallet, “[Formula: see text]-Poincaré invariant orientable field theories with at 1-loop: Scale-invariant couplings, preprint (2018), arXiv:1808.00350 [hep-th]. We see how the role of Fourier transforms is played in this case by Mellin transforms. We briefly discuss the role of transformations and observers.
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9

Padovese, L. R., N. Martin, and F. Millioz. "Time—frequency and time-scale analysis of Barkhausen noise signals." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 223, no. 5 (2009): 577–88. http://dx.doi.org/10.1243/09544100jaero436.

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Carrying out information about the microstructure and stress behaviour of ferromagnetic steels, magnetic Barkhausen noise (MBN) has been used as a basis for effective non-destructive testing methods, opening new areas in industrial applications. One of the factors that determines the quality and reliability of the MBN analysis is the way information is extracted from the signal. Commonly, simple scalar parameters are used to characterize the information content, such as amplitude maxima and signal root mean square. This paper presents a new approach based on the time—frequency analysis. The experimental test case relates the use of MBN signals to characterize hardness gradients in a AISI4140 steel. To that purpose different time—frequency (TFR) and time-scale (TSR) representations such as the spectrogram, the Wigner-Ville distribution, the Capongram, the ARgram obtained from an AutoRegressive model, the scalogram, and the Mellingram obtained from a Mellin transform are assessed. It is shown that, due to nonstationary characteristics of the MBN, TFRs can provide a rich and new panorama of these signals. Extraction techniques of some time—frequency parameters are used to allow a diagnostic process. Comparison with results obtained by the classical method highlights the improvement on the diagnosis provided by the method proposed.
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10

Sasiela, Richard J., and John D. Shelton. "Transverse spectral filtering and Mellin transform techniques applied to the effect of outer scale on tilt and tilt anisoplanatism." Journal of the Optical Society of America A 10, no. 4 (1993): 646. http://dx.doi.org/10.1364/josaa.10.000646.

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