Search results for " Pattern Recognition"
showing 10 items of 1050 documents
Affine camera calibration from homographies of parallel planes
2010
This paper deals with the problem of retrieving the affine structure of a scene from two or more images of parallel planes. We propose a new approach that is solely based on plane homographies, calculated from point correspondences, and that does not require the recovery of the 3D structure of the scene. Neither vanishing points nor lines need to be extracted from the images. The case of a moving camera with constant intrinsic parameters and the one of cameras with possibly different parameters are both addressed. Extensive experiments with both synthetic and real images have validated our approach.
Maximum likelihood for target location in the presence of substitutive noise .
2001
We consider the optimal likelihood algorithm for the estimation of a target location when the images are corrupted by substitutive noise. We show the relationship between the optimal algorithm and the sliced orthogonal nonlinear generalized (SONG) correlation. The SONG correlation is based on the application of a linear correlation to corresponding binary slices of both the input scene and the reference object with appropriate weight factors. For a particular case, we show that the optimal strategy is a function of only the number of pixels for which the gray values in the noisy image match the ones of the reference image when the substitutive noise is uniformly distributed. This is exactly…
Architectural Scenes Reconstruction from Uncalibrated Photos and Map Based Model Knowledge
2001
In this paper we consider the problem of reconstructing architectural scenes from multiple photographs taken from arbitrarily viewpoints. The original contribution of this work is the use of a map as a source of a priori knowledge and geometric constraints in order to obtain in a fast and simple way a detailed model of a scene. We suppose images are uncalibrated and have at least one planar structure as a facade for exploiting the planar homography induced between world plane and image to calculate a first estimation of the projection matrix. Estimations are improved by using correspondences between images and map. We show how these simple constraints can be used to calibrate the cameras, t…
The ATHENA X-ray Integral Field Unit (X-IFU)
2018
Event: SPIE Astronomical Telescopes + Instrumentation, 2018, Austin, Texas, United States.
Left-handed metamaterial coatings for subwavelength-resolution imaging
2012
We report on a procedure to improve the resolution of far-field imaging by using a neighboring high-index medium that is coated with a left-handed metamaterial. The resulting plot can also exhibit an enhanced transmission by considering proper conditions to retract backscattering. Based on negative refraction, geometrical aberrations are considered in detail since they may cause a great impact in this sort of diffraction-unlimited imaging by reducing its resolution power. We employ a standard aberration analysis to refine the asymmetric configuration of metamaterial superlenses. We demonstrate that low-order centrosymmetric aberrations can be fully corrected for a given object plane. For su…
Optoelectronic morphological image processor.
2009
A morphological optoelectronic image processor based on the threshold decomposition concept is described and demonstrated. Binary slices of a gray-scale input image are optically convolved with a binary structuring element of arbitrary size and shape in a noncoherent convolver. The slices are displayed on a liquid-crystal spatial light modulator of 320 × 264 pixels. The kernels are implemented as modifications of the system impulse response. The processor’s convolution patterns are recorded with a CCD camera and fed into a PC by a frame grabber. Subsequent elementary morphological operations are looped. Examples of processing an input image of 256 × 256 pixels and 16 gray levels with kernel…
Variational multiframe restoration of images degraded by noisy (stochastic) blur kernels
2013
This article introduces and explores a class of degradation models in which an image is blurred by a noisy (stochastic) point spread function (PSF). The aim is to restore a sharper and cleaner image from the degraded one. Due to the highly ill-posed nature of the problem, we propose to recover the image given a sequence of several observed degraded images or multiframes. Thus we adopt the idea of the multiframe approach introduced for image super-resolution, which reduces distortions appearing in the degraded images. Moreover, we formulate variational minimization problems with the robust (local or nonlocal) L^1 edge-preserving regularizing energy functionals, unlike prior works dealing wit…
Axial apodization in 4Pi-confocal microscopy by annular binary filters
2002
We present a novel technique for considerably decreasing the sidelobe height of the axial point-spread function of one-photon 4Pi-confocal microscopes. By means of a numerical example, in which the ratio between the excitation and the fluorescence wavelengths was set to epsilon = lambdaexc/lambdadet = 0.8, we show that simply inserting a pair of properly designed two-ring binary masks in the illumination set allows the height of the axial sidelobes to be reduced from 20% to 5% of the height of the central peak. This allows one to receive the full benefit of the strong narrowness of the central lobe provided by the 4Pi-confocal technique.
Invariant pattern recognition based on 1-D Wavelet functions and the polynomial decomposition
1997
Abstract A new filter, consisting of 1-D Wavelet functions is suggested for achieving optical invariant pattern recognition. The formed filter is actually a real function, hence, it is theoretically possible to be implemented under both spatially coherent and spatially incoherent illuminations. The filter is based on the polynomial expansion, and is constructed out of a scaled bank of filters multiplied by 1-D Wavelet weight functions. The obtained output is shown to be invariant to 2-D scaling even when different scaling factors are applied on the different axes. The computer simulations and the experimental results demonstrate the potential hidden in this technique.
A New Set of Quartic Trivariate Polynomial Equations for Stratified Camera Self-calibration under Zero-Skew and Constant Parameters Assumptions
2012
This paper deals with the problem of self-calibrating a moving camera with constant parameters. We propose a new set of quartic trivariate polynomial equations in the unknown coordinates of the plane at infinity derived under the no-skew assumption. Our new equations allow to further enforce the constancy of the principal point across all images while retrieving the plane at infinity. Six such polynomials, four of which are independent, are obtained for each triplet of images. The proposed equations can be solved along with the so-called modulus constraints and allow to improve the performance of existing methods.