Picture Processing Methods Research Articles

Applications of semi-pre-c-open sets

Semi-pre-c-open sets are a subtle development in topology that has a substantial impact on both theoretical investigations and real-world applications. This study explores the several uses of semi-pre-c-open sets in diverse fields. First, we look into how they may be used to improve the structure of generalized topological spaces and give a more comprehensive framework for studying compactness, continuity, and convergence. A more precise categorization of functions is made possible by semi-pre-c-open sets, opening up new function spaces and expanding on previously established findings. Furthermore, their significant applications in digital topology help to advance digital continuity notions and more efficient picture processing methods. We develop and study semi-pre-c-open sets, a novel class of generalized open sets in a topological space. The semi-pre-open sets class includes this class. It is demonstrated that the topology generated by semi-pre-c-open sets is the same. Semi-pre-c-derived set, semi-pre-c-interior points, semi-pre-c-closure, semi-pre-c-closure, semi-pre-c-frontier, and semi-pre-c-exterior are among the topological aspects of these sets that we present and examine. Using examples and counterexamples, the existence of their relationship is also examined.

Facial Skin Texture and Distributed Dynamic Kernel Support Vector Machine (DDKSVM) Classifier for Age Estimation in Facial Wrinkles

Facial wrinkles are common aspects of ageing human skin that may be used in a variety of image-based ageing applications. Wrinkles on the face are 3D skin characteristics that appear as tiny discontinuities or fissures, as well as inconsistencies in the surrounding skin texture. Existing image-based techniques to ageing skin analysis focus on wrinkles as texture rather than curvilinear discontinuity/crack or irregularity characteristics. Picture processing methods are useful for reconstructing and manipulating an image in order to produce various images. The goal of this study is to create a FWDAE-IP (Face Wrinkles Detection and Age Estimate with Image Processing) system that can identify the exact position of wrinkle lines in relation to cracks/ discontinuities, abnormalities, and age estimation using skin texture data from one face image. This FWDAE-IP system is performed based on four major steps: Preprocessing, Skin texture feature extraction, wrinkles detection, and age estimations. In the first step, preprocessing is performed by rotation angle. In the second step, GFs (Gabor Filters), ALTPs (Adaptive Local Ternary Patterns), and AAMs (Active Appearance Models) are introduced against variation in pose or illumination. In the third step, GMM-EM (Gaussian Mixture Model- Expectation-Maximization) is introduced for detecting irregularities in the wrinkles, Gabor filters and image morphology is introduced for detecting discontinuity/crack in the wrinkles. In the fourth step, age estimation is performed based on the detected with wrinkles by DDKSVM (Distributed Dynamic Kernel Support Vector Machine) classifier. The results of age estimation methods are measured via the evaluation metrics such as MAEs (Mean Absolute Error), CSs (Cumulative Scores), accuracy, SSIMs (structural Similarity Indices), and JSIs (Jcard Similarity Indices). The experimentation work is performed based on FG-NET database.

Geometric Evolvement, Simulation, and Test of a Bionic Lateral PDC Reamer Bit Inspired by Capra sibirica Horn.

PDC (polycrystalline diamond compact) bit is the key equipment for drilling holes inside the rock in oil and mining industry. Inspired by the shape and structure of Capra sibirica horn, a bionic lateral PDC reamer bit with variable lateral reaming radius was developed. Side view of Capra sibirica horn was employed for fitting the horn shape curve based on picture processing method. PDC teeth were arranged on the horn shape blade imitating the transverse ridges on the horn to cut the rock material, found with only 30% utilization rate of the total teeth and load concentration of the last tooth. A bionic blade curve evolved from the Capra sibirica horn was defined with geometric method for the lateral reamer bit; the utilization rate of the teeth on the bionic blade curve was improved to 90% with uniformly distributed reaming load. Multigroup simulations were conducted with the finite element method; the effects of bit revolution speed and rotation feed speed of the bionic blade to reaming load were emphatically studied. Concrete sample was reamed indoors from 240 mm to 407 mm in diameter, and the bionic lateral PDC reamer bit was approved by the test result.

Early Classification of Brain Tumor Based on Image Histogram Using Fuzzy-Genetic Algorithm

A Brain Tumor Classification Framework has been outlined and created. The framework uses computer based strategies to identify tumor blocks or lesions and classify the sort of tumor utilizing matching histogram in MRI images of different patients with brain tumors. The picture processing methods such as picture segmentation, picture enhancement. Several techniques can classify the tumor such as Support vector machine (SVM), artificial neural networks (ANN), and Naive Bayes, but they did not accomplish the required accuracy. The automatic classification of tumors requires high precision since the non-accurate conclusion would cause a rise within the predominance of more serious diseases. In this paper, the proposed method using fuzzy logic and genetic algorithm based on image histogram to enhance the brain tumor classification. The experimental result showed that our technique is more effective than the previous techniques, as well as the classification accuracy efficiency is 99.9%.

Distribuição do sistema radicular do milho em terra roxa estruturada latossólica: II. Comparação entre cultura irrigada e fertirrigada

A distribuição do sistema radicular do milho irrigado, até 1 m de profundidade, em uma terra roxa estruturada latossólica em Piracicaba, SP, foi analisada aos 126 dias após a emergência das plantas. As raízes expostas pela abertura de trincheiras longitudinalmente às Unhas de plantas foram filmadas e essas imagens digitalizadas e processadas para a contabilização de sua distribuição no perfil do solo, por meio do sistema SIARCS desenvolvido para esse fim. A densidade de raiz de milho a 0-60 cm foi maior para a aplicação de N via solo, enquanto que a 60-100 cm a fertirrigação proporcionou uma maior presença de raízes. Por meio de tensiômetros e da sonda de nêutrons, notou-se, respectivamente, que a maior amplitude de variação do potencial matricial da água no solo e da quantidade de água armazenada no solo ocorreu até a profundidade de 50 cm, evidenciando a boa correspondência dessas técnicas com o método de processamento de imagens.

The application of transport theory to visualization of 3-D scalar data fields

This paper describes a general visualization model for 3-D scalar data fields based on linear transport theory that contains common volume rendering models as special cases and/or approximations. The concept of ‘‘virtual’’ particles for the extraction of information from data fields is introduced. The role of different types of interaction of the data field with those particles such as absorption, scattering, source, and color shift are discussed and demonstrated. Special attention is given to possible tools for the enhancement of interesting data features. Random distortions or noise of the data field are mapped onto the image plane in a well-defined way such that picture processing methods can be used to reconstruct the appearance of the undistorted data set. Random texturing can provide visual insights as to the magnitude and distribution of deviations of related data fields, e.g., originating from analytic models and measurements, or in the noise content of a given data field. Hidden symmetries of a data set can often be identified visually by allowing it to interact with a preselected beam of ‘‘physical’’ particles with the attendant appearance of characteristic structural effects such as channeling.

Volume rendering and data feature enhancement

This paper describes a general visualization model for 3D scalar data fields based on linear transport theory which contains common volume rendering models as special cases and/or approximations. The concept of "virtual" particles for the extraction of information from data fields is introduced. The role of different types of interaction of the data field with those particles such as absorption, scattering, source and color shift are discussed and demonstrated.Special attention is given to possible tools for the enhancement of interesting data features. Random distortions or noise of the data field are mapped onto the image plane in a well-defined way such that picture processing methods can be used to reconstruct the appearance of the undistorted data set. Random texturing can provide visual insights as to the magnitude and distribution of deviations of related data fields, e.g., originating from analytic models and measurements, or in the noise content of a given data field. Hidden symmetries of a data set can often be identified visually by allowing it to interact with a preselected beam of "physical" particles with the attendant appearance of characteristic structural effects such as channeling.

Binarization of scanning Moiré fringe pattern

This paper describes a digital picture processing method to obtain a binary scanning moiré pattern. In this method, a bias component due to the illumination light distribution is eliminated from the scanning moiré fringe pattern to detect the zero-crossing points of the moiré profile. The binary fringe pattern is then obtained from the zero-crossing points. Experiments indicate that the method is useful for facilitating three-dimensional automatic measurement using moiré topography.

Improving dynamic programming to solve image registration

A new method of dynamic programming (DP) is presented. A picture is paired with a reference map. In order to arrive at picture registration, an ordered sequence of primitive patterns is formed from the map. An attempt is made to locate a similar sequence from the picture using classical picture processing methods. This yields a distorted and unordered sequence marked by noise. DP is then used to search for a common match to the two sequences. Both the initial and final registration states are, however, unknown. Moreover, the continuity of the path is frequently interrupted, due to shortcomings in detection, or perhaps occlusions. Thus, classical DP algorithms appear to give only poor results under practical conditions. When well-adapted to treat signals issued from a first order Markovian process, they can be used, as this method shows, to treat kth order processes. The concept of the “virtual state”, kept in memory, suspends broken paths until they can be reconnected, thus bridging the existing gaps between the different parts of the path. The proposed algorithm has been applied to satellite images with their contours sectioned by clouds. The result leads to the guarantee of very good registration, in spite of image contours badly hampered by noise and/or clouds.

A Method of Fuzzy‐Theory‐Based Computer‐Aided Exploratory Data Analysis

AbstractWhen evaluating functional relationships from given data in an exploratory state of investigation, we only want to get an imagination of a possibly existing trend. Usually, methods of local or empirical regression are chosen to meet this purpose. In the paper we suggest an alternative using the possibilities of modern picture processing methods and computers. The data were transformed into a grey‐tone picture representing a fuzzy observation set, the maximum trace of which yields the desired first impression of the trend and may serve as the starting point for further detailed evaluation of the functional relationship. The method is illustrated by a real‐data numerical example.

Experiments on the characterization of metamorphic textures from a micrograph of an amphibolite

SUMMARYPicture processing using generalized instrumentation with specially developed software, and image analysis by means of a Quantimet 720 image analyser with a linear correlator, were employed in the study of rock textures. The boundaries of all individual grains from a portion of a thin section of a rock were distinguished and hand‐drafted for digitization and analysis. From the grey level image of boundaries of the profiles of the grains, obtained by hexagonal scanning of line drawings, binary images were produced for each phase and used for textural measurements. Ink drawings extracted from the boundary pattern were also used for the image analyser experiments.In picture processing experiments, programmed structuring elements of different shapes and two‐dimensional autocorrelation functions were used to characterize morphology and spatial distribution of the different phases. Transformations of binary images were programmed at the bit level to reduce storage requirements and computing time. In Quantimet 720 experiments, linear erosion and histogram of sizes were used for computing the mean dimensions of the grains. Periodical arrangements were studied by means of the covariance function.This contribution uses simple texture measures derived from mathematical morphology and picture processing methods, in order to assess the feasibility of two different technical approaches in the analysis of the same material. The extraction of image information from the material analysed, which was not attempted before, is cumbersome and technically complex. This difficulty is partly responsible of why little is known on the quantitative characterization of metamorphic textures from thin sections.

The quantification of blood cell motion by a method of automatic digital picture processing

In order to facilitate the study of cell movement, the paper introduces a new automatic picture processing method for tracking and quantifying the dynamics of blood cell motion. The input to the program is a 16 mm cine film of the cell culture viewed in a steady condition. Under the circumstances, the global directional movement tendencies of the group of cells under consideration can be characterized by a Markov chain model. By observing and quantifying the cell paths, it is possible, using this model, to determine the probability that the cell population is moving in a particular direction. This information might be of interest in the study of the effect of substances on cell movement, defects in white blood cell migration, and the general interaction among cells.