Los momentos de Krawtchouk y Tchebichef y sus aplicaciones en el procesamiento de imágenes digitales (Revisión)

In this article, there is an overview of Krawtchouk and Tchebichef´s orthogonal discreet polynomials, which have dissimilar on-the-job applications with digital imagery. A brief historic introduction is given, and then, the theory of these polynomials is summarized. Finally, a brief section with some of the most significant applications of these on-the-job polynomials with digital imagery is presented.En este artículo se brinda una visión de los polinomios ortogonales discretos de Krawtchouk y Tchebichef, los cuales tienen disímiles aplicaciones en el trabajo con imágenes digitales. Se comienza dando una breve introducción histórica y seguidamente se resume  la teoría de estos polinomios. Finalmente se presenta un breve apartado con algunas de las aplicaciones más significativas de estos polinomios en el trabajo con imágenes digitales

On the validation of solid mechanics models using optical measurements and data decomposition

Engineering simulation has a significant role in the process of design and analysis of most engineered products at all scales and is used to provide elegant, light-weight, optimized designs. A major step in achieving high confidence in computational models with good predictive capabilities is model validation. It is normal practice to validate simulation models by comparing their numerical results to experimental data. However, current validation practices tend to focus on identifying hot-spots in the data and checking that the experimental and modeling results have a satisfactory agreement in these critical zones. Often the comparison is restricted to a single or a few points where the maximum stress/strain is predicted by the model. The objective of the present paper is to demonstrate a step-bystep approach for performing model validation by combining full-field optical measurement methodologies with computational simulation techniques. Two important issues of the validation procedure are discussed, i.e. effective techniques to perform data compression using the principles of orthogonal decomposition, as well as methodologies to quantify the quality of simulations and make decisions about model validity. An I-beam with open holes under three-point bending loading is selected as an exemplar of the methodology. Orthogonal decomposition by Zernike shape descriptors is performed to compress large amounts of numerical and experimental data in selected regions of interest (ROI) by reducing its dimensionality while preserving information; and different comparison techniques including traditional error norms, a linear comparison methodology and a concordance coefficient correlation are used in order to make decisions about the validity of the simulation

Unocculuded object grasping by using visual data

Automatic grasping objects can become important in the areas such as industrial processes, processes which are dangerous for human, or the operations which should be executed in the places, small for people work. In this study, it is aimed to design a robotic system for grasping unocculuded certain objects by using visual data. For this aim an experimental process was implemented. Visual data process can be divided in two main parts: identification and three dimensional positioning. Identification issue suffers from several conditions as rotation, camera position, and location of the subject in the frame. Also obtaining the features invariant from these conditions is important. Therefore Zernike moment method can be used to overcome these negativities. In order to identify the objects an artificial neural network was used to classify the objects by using Zernike moment coefficients. In the experimental system a parallel axis stereovision subsystem, a DSPFPGA embedded media processor, and five-axis robot arm were used. The success rate of artificial neural network was 98%. After identifying the objects, a sequential algebra were performed in the DSP part of the media processor and the position of the object according to robot arm reference point was extracted. After all, desired object in the instant frame was grasped and placed in different location by the robot arm

A hybrid framework for nonlinear dynamic simulations including full-field optical measurements and image decomposition algorithms

Innovative designs of transport vehicles need to be validated in order to demonstrate reliability and provide confidence. It is normal practice to study the mechanical response of the structural elements by comparing numerical results obtained from finite element simulation models with results obtained from experiment. In this frame, the use of wholefield optical techniques has been proven successful in the validation of deformation, strain, or vibration modes. The strength of full-field optical techniques is that the entire displacement field can be acquired. The objective of this article is to integrate full-field optical measurement methodologies with state-of-the-art computational simulation techniques for nonlinear transient dynamic events. In this frame, composite car bonnet frame structures of dimensions about 1.8 m 30.8 m are considered. They have been tested in low-velocity mass-drop impact loading with impact energies ranging from 20 to 200 J. In parallel, simulation models of the car bonnet frame have been developed using layered shell elements. The Zernike shape descriptor approach was used to decompose numerical and experimental data into moments for comparison purposes. A very good agreement between numerical and experimental results was observed. Therefore, integration of numerical analysis with full-field optical measurements along with sophisticated comparison techniques can increase design reliability

Brain White Matter Hyperintensity Lesion Characterization in T2 Fluid-Attenuated Inversion Recovery Magnetic Resonance Images: Shape, Texture, and Potential Growth

Prior methods in characterizing age-related white matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance images (MRI) have mainly been limited to understanding the sizes of, and occasionally the locations of WMH lesions. Systematic morphological characterization has been missing. In this work, we proposed innovative methods to fill this knowledge gap. We developed an innovative and proof-of-concept method to characterize and quantify the shape (based on Zernike transformation) and texture (based on fuzzy logic) of WMH lesions. We have also developed a multi-dimension feature vector approach to cluster WMH lesions into distinctive groups based on their shape and then texture features. We then developed an approach to calculate the potential growth index (PGI) of WMH lesions based on the image intensity distributions at the edge of the WMH lesions using a region-growing algorithm. High-quality T2 FLAIR images containing clearly identifiable WMH lesions with various sizes from six cognitively normal older adults were used in our method development Analyses of Variance (ANOVAs) showed significant differences in PGI among WMH group clusters in terms of either the shape (P = 1.06 × 10−2) or the texture (P < 1 × 10−20) features. In conclusion, we propose a systematic framework on which the shape and texture features of WMH lesions can be quantified and may be used to predict lesion growth in older adults

Analysis of the image moments sensitivity for the application in pattern recognition problems

Momenti slike su numerički deskriptori koji sadrže informaciju o svojstvima invarijantnim na translaciju, rotaciju, promjenu skale i neke oblike distorzije, a njihova analiza je jedna od metoda koje se često koriste pri analizi slika i raspoznavanju uzoraka. U okviru ove radnje razvijeni su algoritmi za računanje geometrijskih, Legendreovih, Zernikeovih, Fourier – Mellinovih te tri tipa Fourier – Jacobijevih momenata, kao i iz njih definiranih invarijanti slike u programskom jeziku MatLab uz rješavanje inverznog problema rekonstrukcije početnog ulaza. Za sve tipove momenata osim najjednostavnijih geometrijskih definirani su vektori osjetljivosti na rotaciju i promjenu skale čije su komponente oni članovi skupa koji nose značajnije informacije o ulaznoj slici. Primjenom novih deskriptora na klasifikaciju rukom pisanih slova i identifikacijskih fotografija osoba pokazano je da je relevantna informacija o ulazu na taj način sačuvana, a njihov je izračun znatno brži i jednostavniji uz zadržanu sposobnost jednoznačnog raspoznavanja uzoraka. Korištenjem momenata slike i vektora osjetljivosti analizirani su znakovi s dvaju glagoljskih spomenika te utvrđeno postojanje mješavine znakova trokutastog i okruglog modela glagoljice. Metoda je primijenjena i na klasifikaciju tragova puzanja ličinki mutanata vinske mušice za potrebe proučavanja odgovora živčanog sustava na različite podražaje.Image moments are numerical descriptors invariant to translation, rotation, change of scale and some types of image distortion and their analysis is one of the most often used methods in image processing and pattern recognition. In this work, algorithms for calculation of geometric, Legendre, Zernike, Fourier – Mellin and three types of Fourier – Jacobi moments were implemented in MatLab. Hu's, affine and blur invariants were also obtained as well as inverse problem of input image reconstruction solved. For each type of image moments exept geometric ones the set of sensitivity vectors for rotation and scale were defined. Their components are those image moments which describe more important features of the input image. These new descriptors were applied for classification of handwritten letters and identifying personal photos. It was shown that the process of such descriptor calculation is much faster and simpler while preserving all the relevant information about input image. Using this method, the signs carved in two glagolitic inscriptions were analyzed and the mixture of triangular and round glagolitic letters found. The method was also applied to classification of the mutant fruit fly larvae crawling trails which is needed in studying responses of the nervous system to different stimuli