Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is efficient, has very few free parameters to tune, and the authors show how to tune the few remaining parameters. Results show that the method reliably aligns various datasets including two facial datasets and two medical datasets of prostate and brain MRI images and demonstrates efficiency in terms of performance and a reduction of the computational cost.
Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data. This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −
Films of PMMA and copper sulphate doped PMMA have been prepared by casting method. Absorbance and transmittance spectra were recorded in the wavelength range (300-900) nm in order to calculate, single oscillator energy, dispersion energy, average oscillator strength, the refractive index at infinite wavelength, M-1 and M -3 moments of the optical spectra, it was found that all these parameters were effected by doping.
Most heuristic search method's performances are dependent on parameter choices. These parameter settings govern how new candidate solutions are generated and then applied by the algorithm. They essentially play a key role in determining the quality of the solution obtained and the efficiency of the search. Their fine-tuning techniques are still an on-going research area. Differential Evolution (DE) algorithm is a very powerful optimization method and has become popular in many fields. Based on the prolonged research work on DE, it is now arguably one of the most outstanding stochastic optimization algorithms for real-parameter optimization. One reason for its popularity is its widely appreciated property of having only a small number of par
... Show MoreIn this work the diode planer magnetron sputtering device was
designed and fabricated. This device consists of two aluminum discs
(8cm) diameter and (5mm) thick. The distance between the two
electrodes is 2cm, 3cm, 4cm and 5cm.
Design and construction a double probe of tungsten wire with
(0.1mm) diameter and (1.2mm) length has been done to investigate
electron temperature, electron and ion density under different
distances between cathode and anode. The probes were situated in
the center of plasma between anode and cathode.
The results of this work show that, when the distance between
cathode and anode increased, the electron temperature decreased.
Also, the electron density increases with the increasing
In this research, the results of x-ray diffraction method were used to determine the uniform stress deformation and microstructure parameters of CuO nanoparticles to determine the lattice strain obtained and crystallite size and then to compare the results obtained by two model Halder Wagner and Size Strain Plot with the results of these methods of the same powder using equations during which the calculation of the size of the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (19.81nm) and the lattice strain (0.004065) of the Halder-wagner model respectively and for the ssp method were the results of the crystallite size (17.20nm) and lattice strain (0.000305) respectively. The sa
... Show MoreAn experiment was carried out in the vegetables field of Horticulture Department / College of Agriculture / Baghdad University , for the three seasons : spring and Autumn of 2005 , and spring of 2007 , to study the type of gene action in some traits of vegetative , flowery growth , yield and its components in summer squash crosses (4 x 3 = cross 1 , 3 x 7 = cross 2 , 3 x 4 = cross 3 , 3 x 5 = cross 4 , 5 x 1= cross 5 , 5 x 2 = cross 6). The study followed generation mean analysis method which included to each cross (P1 , P2 , F1 , F2 , Bc1P1 , Bc1P2) , and those populations obtained by hybridization during the first and second seasons. Experimental comparison was performed in the second (Two crosses only) and third seasons , (four crosses)
... Show MoreOne of the most common public liver diseases over the world is fatty liver which contain alcoholic and non-alcoholic fatty liver. One-fourth among general population are impact Non-Alcoholic Fatty Liver Disease (NAFLD) in the worldwide.Retinol binding protein 4 (RBP4) is known as an adipokine, mainly synthesized and secreted from the liver and form adipose tissues. RBP4 acts as a transporter and specifically bound to retinol from liver to others tissues. Visfatin is an adipocytokine and mainly produced from visceral fat tissue, skeletal muscles as well as liver. Vitamin A absorbed, transported as retinyl esters to the liver then hydrolyzed to the retinol form and storage in hepatic stellate cells (HSCs) after reesterified with rigly
... Show MoreRecently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse
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