908 resultados para Image processing -- Digital techniques


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The Ag-NOR staining technique and image analysis were used to evaluate morphological parameters (area, perimeter and axis ratio) in nucleoli from normal thyroids and from thyroids bearing proliferating lesions (carcinomas, adenomas and hyperplasias). Regions with normal appearance located close to adenomatous and carcinomatous regions, in the thyroid of every patient, were also analyzed for comparison with the respective pathological regions and with normal thyroids. Statistical analysis of data for the nucleolar area and perimeter allowed the separation of adenomas and carcinomas from hyperplasias and normal tissue but not the two components in each of these two groups. However, if we look at the numbers, a sequence of increasing nucleolar mean areas in the order: normal, hyperplasia, adenoma and carcinoma may be observed, indicating the sequence of increasing rRNA requirements in these different kinds of cells. The axis ratio that denotes the nucleolar shape (round or oblong) did not show significant differences among tissues, suggesting that shape is not important in the characterization of these pathologies. Differences in nucleolar areas and perimeter between normal and affected regions from each patient were statistically significant for adenomas and carcinomas. When these normal regions were compared with the normal thyroids, significant differences were not obtained in the three evaluated parameters. The observations and their importance for histopathological diagnosis are discussed.

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This article introduces a new method for 3-dimensional dental cast analysis, by using a mechanical 3-dimensional digitizer, MicroScribe 3DX (Immersion, San Jose, Calif), and TIGARO software (not yet released, but available from the author at hayasaki@dent.kyushu-u.ac.jp). By digitizing points on the model, multiple measurements can be made, including tooth dimensions; arch length, width, and perimeter; curve of Spee; overjet and overbite; and anteroposterior discrepancy. The bias of the system can be evaluated by comparing the distance between 2 points as determined by the new system and as measured with digital calipers. Fifteen pairs of models were measured digitally and manually, and the bias was evaluated by comparing the variances of both methods and checking for the type of error obtained by each method. No systematic errors were found. The results showed that the method is accurate, and it can be applied to both clinical practice and research. Copyright © 2005 by the American Association of Orthodontists.

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The Paraguay River is the main tributary of the Paraná River and has an extension of 1.693 km in Brazilian territory. The navigability conditions are very important for the regional economy because most of the central-west Brazilian agricultural and mineral production is transported by the Paraguay waterway. Increased sedimentation along the channel requires continuous dredging to waterway maintenance. Systematic bathymetric surveys are periodically carried out in order to check depth condition along the channel using echo-sounding devices. In this paper, digital image processing and geostatistical analysis methods were used to analyze the applicability of the ASTER sensor to estimate channel depths in a segment of the upper Paraguay River. The results were compared with field data in order to choose the band with better adjustment and to evaluate the standard deviation. Comparing the VNIR bands, the best fit was presented by the red wavelength (band 2; 0,63 - 0,69 μm), showing a good representation of the channel depths shallow than 1,7 m. Applying geostatistical methods, the model accuracy was enhanced from 43 cm to 36 cm and undesired components were slacked. It was concluded that the digital number of band 2, converted to bathymetry information allows a good estimation of river depths and channel morphology.

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This paper describes the development of a mechatronic system for a predictive maintenance grounded on wear particle analysis. The reckoning of wear particles containing in lubricating industrial oils brings the image acquisition system into being. The ISO 4406:1999 standard is a guide to establish the counting and evaluation processes of particles. The system applied to the acquisition and analysis of the data consists of a digital camera, a monocular microscope and an oil filtering system. A computational program was developed with the application of Visual Microsoft C++ in a way to detain the oil sample image from the microscope slide to the computer screen. Quantitative analyses of the wear debris particles bulk are exploited applying a graphical interface that was developed to render the image processing of the sample test. The implemented system has a reachable cost thus it can be applied for schooling goals and for bolstering laboratories of minor industries and medium size companies.

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Soil use for the development of activities as agriculture and livestock has been causing great alterations in the environment, mainly when these are practiced intensively, disrespecting the fragility and aptitude of the natural resources. Therefore, it is essential that the planning of the agricultural activities is done, taking into consideration the several environmental criteria involved in the decision-making process. Thus, this study aimed to analyze the agricultural aptitude classes of lands from a watershed through geographical information system (GIS). The Arroio Ajuricaba watershed is located in the Municipality of Marechal Cândido Rondon - PR among the coordinates UTM 787309m E and 793892m E; 7275026m N and 7281310m N, in the Spindle 21, presenting an area of 1681ha. Soil maps, in semi detail scale, was the digital cartographic base used. The results allowed to conclude that 42.41% of the basin presented a good aptitude for farming in handling level of high technology (handling level C), regular aptitude for B, and restricted aptitude for A [class 1(a)bC] and that 12% of the area had regular aptitude for farming in the three handling levels (class 1abc). The watershed lands (14.24%) presented regular aptitude for farming in handling level C, restricted aptitude for B, and inapt for A [class of aptitude 2(b)c]; 15.85% presented good aptitude for planted pasture (class 4P) and 12.21% were considered without aptitude for agricultural use (class 6). We can say that 71.94% of the lands has aptitude for farming, although they present different degrees of limitations that request different treatments for its conservation.

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The aim of this study was to evaluate whether digitized images obtained from occlusal radiographs taken with low or over dose of radiation could be improved with the aid of computer software for digital treatment. Thirteen occlusal radiographs of a dry skull were taken employing 13 different exposure times. The radiographs were digitized and then manipulated with the program for image editing. 143 evaluations were performed by specialists in dental radiology who classified radiographs as appropriate or not appropriate for interpretation. Test Z was used for statistical analysis of the data and the results showed that it is possible to manipulate digitized radiographic images taken with 75% of the ideal exposure time and to make them suitable for interpretation and diagnosis. Conversely, it was concluded that the over exposed images, 57.50% above the standard exposure time, were inadequate.

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Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 2011 IEEE.

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The pathogens manifestation in plantations are the largest cause of damage in several cultivars, which may cause increase of prices and loss of crop quality. This paper presents a method for automatic classification of cotton diseases through feature extraction of leaf symptoms from digital images. Wavelet transform energy has been used for feature extraction while Support Vector Machine has been used for classification. Five situations have been diagnosed, namely: Healthy crop, Ramularia disease, Bacterial Blight, Ascochyta Blight, and unspecified disease. © 2012 Taylor & Francis Group.

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Nowadays, systems based on biométrie techniques have a wide acceptance in many different areas, due to their levels of safety and accuracy. A biometrie technique that is gaining prominence is the identification of individuals through iris recognition. However, to be proficiently used these systems must process their recognition task as fast as possible. The goal of this work has been the development of an iris recognition method to produce results rapidly, yet without losing the recognition accuracy. The experimental results show that the method is quite promising. © 2012 Taylor & Francis Group.

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Duplex and superduplex stainless steels are class of materials of a high importance for engineering purposes, since they have good mechanical properties combination and also are very resistant to corrosion. It is known as well that the chemical composition of such steels is very important to maintain some desired properties. In the past years, some works have reported that γ 2 precipitation improves the toughness of such steels, and its quantification may reveals some important information about steel quality. Thus, we propose in this work the automatic segmentation of γ 2 precipitation using two pattern recognition techniques: Optimum-Path Forest (OPF) and a Bayesian classifier. To the best of our knowledge, this if the first time that machine learning techniques are applied into this area. The experimental results showed that both techniques achieved similar and good recognition rates. © 2012 Taylor & Francis Group.

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Objective: Assess the occurrence of secondary brow ptosis after upper lid blepharoplasty. Methods: Forty-five individuals (n90 brows) submitted to upper lid blepharoplasty, were assessed by means of a comparative analysis using pre- and post-operatively digital photographs, in the primary position of the eye. The images were processed using ImageJ software, transferred to a computer, to an electronic Microsoft Excel 2002® worksheet. Angular measurements were used, taking the lateral canthal angle of the brow, the most medial point of the brow, the medial canthal angle and the lateral canthal angle of the lid as anatomical reference points. When the outer angles were reduced or the inner angles increased after surgery this was considered a brow ptosis. Individuals who had undergone lid surgery associated with the eyebrow, previous eyebrow surgery and those with eyelid ptosis were excluded. The difference between the pre-operative and post-operative measurements were analyzed statistically using the Student's t-test for paired samples and the angular variation was compared with their corresponding contralateral sample using Wilcoxon's non-parametric test. Results: The measurements obtained after the blepharoplasty show significant variations from those before the surgery, indicating that the correction of redundant tissues in the brow accentuates the tendency of the eyebrow to move down. The alterations are more important in the lateral portion of the eyebrow and they occur bilaterally. Conclusion: The assessment of angular measurements obtained pre- and post-operatively showed that there are secondary changes in the position of the eyebrow as a result of upper eyelid blepharoplasty. © 2012 Informa Healthcare USA, Inc.

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This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.

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Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. © 2012 IEEE.

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Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be in-viable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the bats behaviour, which has never been applied to this context so far. The wrapper approach combines the power of exploration of the bats together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in five public datasets have demonstrated that the proposed approach can outperform some well-known swarm-based techniques. © 2012 IEEE.

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Correlative fractography is a new expression proposed here to describe a new method for the association between scanning electron microscopy (SEM) and light microscopy (LM) for the qualitative and quantitative analysis of fracture surfaces. This article presents a new method involving the fusion of one elevation map obtained by extended depth from focus reconstruction from LM with exactly the same area by SEM and associated techniques, as X-ray mapping. The true topographic information is perfectly associated to local fracture mechanisms with this new technique, presented here as an alternative to stereo-pair reconstruction for the investigation of fractured components. The great advantage of this technique resides in the possibility of combining any imaging methods associated with LM and SEM for the same observed field from fracture surface. © Microscopy Society of America 2013.