Construction and test of low cost X-ray tomography scanner for physical-chemical analysis and nondestructive inspections

X-ray computed tomography (CT) refers to the cross-sectional imaging of an object measuring the transmitted radiation at different directions. In this work, we describe the development of a low cost micro-CT X-ray scanner that is being developed for nondestructive testing. This tomograph operates using a microfocus X-ray source and contains a silicon photodiode as detectors. The performance of the system, by its spatial resolution, has been estimated through its Modulation Transfer Function - MTF and the obtained value at 10% of MTF is 661 μm. It was built as a general purpose nondestructive testing device. © 2009 American Institute of Physics.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

Proposição de rotina morfológica para detecção de malha viária em imagens orbitais

The outdating of cartographic products affects planning. It is important to propose methods to help detect changes in surface. Thus, the combined use of remote sensing image and techniques of digital image processing has contributed significantly to minimize such outdating. Mathematical morphology is an image processing technique which describes quantitatively geometric structures presented in the image and provides tools such as edge detectors and morphological filters. Previous studies have shown that the technique has potential on the detection of significant features. Thus, this paper proposes a routine of morphological operators to detect a road network. The test area corresponds to an excerpt Quickbird image and has as a feature of interest an avenue of the city of Presidente Prudente, SP. In the processing, the main morphological operators used were threshad, areaopen, binary and erosion. To estimate the accuracy with which the linear features were detected, it was done the analysis of linear correlation between vectors of the features detected and the corresponding topographical map of the region. The results showed that the mathematical morphology can be used in cartography, aiming to use them in conventional cartographic updating processes.

Effect of phosphate-bonded investments on titanium reaction layer and crown fit

This study analyzed the reaction layer and measured the marginal crown fit of cast titanium applied to different phosphate-bonded investments, prepared under the following conditions (liquid concentration/casting temperature): Rema Exakt (RE) - 100%/237°C, 75%/287°C, Castorit Super C (CS)-100%/70°C, 75%/141°C and Rematitan Plus (RP)-100%/430°C (special to titanium cast, as the control group). The reaction layer was studied using the Vickers hardness test, and analyzed by two way ANOVA and Tukey's HSD tests (α = 0.05). Digital photographs were taken of the crowns seated on the die, the misfit was measured using an image analysis system and One-way ANOVA, and Tukey's test was applied (α = 0.05). The hardness decreased from the surface (601.17 VHN) to 150 μm (204.03 VHN). The group CS 75%/141°C presented higher hardness than the other groups, revealing higher surface contamination, but there were no differences among the groups at measurements deeper than 150 μm. The castings made with CS - 100%/70°C presented the lowest levels of marginal misfit, followed by RE -100%/237°C. The conventional investments CS (100%) and RE (100%) showed better marginal fit than RP, but the CS (75%) had higher surface contamination.

Fast petroleum well drilling monitoring through optimum-path forest

Automatic inspection of petroleum well drilling has became paramount in the last years, mainly because of the crucial importance of saving time and operations during the drilling process in order to avoid some problems, such as the collapse of the well borehole walls. In this paper, we extended another work by proposing a fast petroleum well drilling monitoring through a modified version of the Optimum-Path Forest classifier. Given that the cutting's volume at the vibrating shale shaker can provide several information about drilling, we used computer vision techniques to extract texture informations from cutting images acquired by a digital camera. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and effciency. We used the Optimum-Path Forest (OPF), EOPF (Efficient OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP) Support Vector Machines (SVM), and a Bayesian Classifier (BC) to assess the robustness of our proposed schema for petroleum well drilling monitoring through cutting image analysis.

Flexibility and torsional resistance of three nickel-titanium retreatment instrument systems

Aim To assess the dimensional characteristics, flexibility and torsional behaviour of nickel-titanium retreatment instruments. Methodology Using image analysis software and high-resolution digital images, the instrument length, tip angle, diameter at 3mm from the tip and the distance between the blades (pitch length) of the following eight instruments were measured (n=12 for each measurement parameter): the ProTaper Universal retreatment (PTU-R) D1, D2 and D3 instruments; the R-Endo R1, R2 and R3 retreatment instruments; and the Mtwo retreatment (Mtwo-R) sizes 25 and 15 retreatment instruments. Maximum torque and the angular deflection at fracture as well as the bending moment at 45° were measured (n=12) according to the International Standards Organisation (ISO) specification number 3630-1. Data were analysed using the analysis of variance (α=0.05). Results The length of the active part of the instruments was found to vary according to the depth of the canal into which they were designed to reach. The pitch length also increased along the active length. The PTU-R D1 and the Mtwo-R instruments had active tips. Measurements of the bending moment at 45° revealed that the Mtwo-R 15 instrument was the most flexible, whereas the PTU-R D1 was the least flexible. The maximum torque tended to increase as the instrument diameter at 3mm from the tip increased, whereas the angular deflection at fracture varied in the opposite direction. Conclusions The geometrical characteristics of the retreatment instruments and their flexibility and torsion behaviour were consistent with their intended clinical application. © 2011 International Endodontic Journal.

Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.

Image categorization through optimum path forest and visual words

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.

A computer vision approach to quantify leaf anatomical plasticity: A case study on gochnatia polymorpha (less.) cabrera

Inferences about leaf anatomical characteristics had largely been made by manually measuring diverse leaf regions, such as cuticle, epidermis and parenchyma to evaluate differences caused by environmental variables. Here we tested an approach for data acquisition and analysis in ecological quantitative leaf anatomy studies based on computer vision and pattern recognition methods. A case study was conducted on Gochnatia polymorpha (Less.) Cabrera (Asteraceae), a Neotropical savanna tree species that has high phenotypic plasticity. We obtained digital images of cross-sections of its leaves developed under different light conditions (sun vs. shade), different seasons (dry vs. wet) and in different soil types (oxysoil vs. hydromorphic soil), and analyzed several visual attributes, such as color, texture and tissues thickness in a perpendicular plane from microscopic images. The experimental results demonstrated that computational analysis is capable of distinguishing anatomical alterations in microscope images obtained from individuals growing in different environmental conditions. The methods presented here offer an alternative way to determine leaf anatomical differences. © 2013 Elsevier B.V.

Equine tendonitis therapy using mesenchymal stem cells and platelet concentrates: A randomized controlled trial

Introduction. Tendon injury is a major cause of lameness and decreased performance in athletic equines. Various therapies for tendonitis have been described; however, none of these therapies results in complete tissue regeneration, and the injury recurrence rate is high even after long recovery periods involving rest and physiotherapy. Methods. A lesion was induced with collagenase gel in the superficial digital flexor tendon in the center portion of the metacarpal region of eight equines of mixed breed. After two weeks, the lesions of the animals in the treated and control groups were treated through the intralesional administration of mesenchymal stem cells derived from adipose tissue (adMSCs) suspended in platelet concentrate (PC) and with phosphate buffered saline (PBS), respectively. Serial ultrasound analyses were performed every two weeks. After 16 weeks of therapy, a biopsy was performed for histopathological, immunohistochemical and gene expression (type I collagen (COL1A1), type III collagen (COL3A1), tenascin-C (TNC), tenomodulin (TNMD), and scleraxis (SCX)) analyses. Results: Differences in the ultrasound and histopathological analyses were observed between the groups. Improved results were reported in the group treated with adMSCs suspended in PC. There was no difference in the gene expression levels observed after the different treatments. The main results observed from the histopathological evaluation of the treated group were as follows: a prevention of the progression of the lesion, a greater organization of collagen fibers, and a decreased inflammatory infiltrate. A lack of progression of the lesion area and its percentage was observed in the ultrasound image, and increased blood flow was measured by Power Doppler. Conclusions: The use of adMSCs combined with PC for the therapy of experimentally induced tendonitis prevented the progression of the tendon lesion, as observed in the ultrasound examination, and resulted in a greater organization and decreased inflammation, as observed in the histopathological evaluation. These data demonstrate the therapeutic potential of this therapy for the treatment of equine tendonitis. © 2013 Carvalho et al.; licensee BioMed Central Ltd.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Automated diagnosis of human intestinal parasites using optical microscopy images

Intestinal parasitosis constitutes a serious health problem in most tropical countries. The diagnosis of enteroparasites in laboratory routine relies on the examination of stool samples using optical microscopy and the error rates usually range from moderate to high. Approaches based on automatic image analysis have been proposed, but the methods are usually specific for some species, some of them are computationally expensive, and image acquisition and focus are manual. We present a solution to automate the diagnosis of the 15 most common species of enteroparasites in Brazil, using a sensitive parasitological technique, a motorized microscope with digital camera for automatic image acquisition and focus, and fast image analysis methods. The results indicate that our solution is effective and suitable for laboratory routine, in which the exam must be concluded in a few minutes. © 2013 IEEE.

Dental fluorescence: Potential forensic use

In cases of identification of bones, skeletal segments or isolated bones, searching for biotypologic diagnostic data to estimate an individual's age enables comparing these data with those of missing individuals. Enamel, dentin and pulp undergo remarkable changes during an individual's life. The enamel becomes more mineralized, smoother and thinner, and deteriorates because of physiological and pathological factors. Dental pulp decreases in volume due to the deposition of secondary dentin; thus, the dentin becomes thicker with time. In natural teeth, the fluorescence phenomenon occurs in dentin and enamel and changes in those tissues may alter the expression of the natural tooth color. The aim of this study was to assess the correlation between age and teeth fluorescence for individuals from different age groups. The sample consisted of 66 randomly selected Brazilians of both genders aged 7-63 years old. They were divided into 6 groups: Group 1 - aged 7-12 years, Group 2 - aged 13-20 years, Group 3 - aged 21-30 years, Group 4 - aged 31-40 years, Group 5 - aged 41-50 years and Group 6 - aged between 51 and 63 years. Upper right or left central incisors were used for the study. Restored and aesthetic rehabilitated teeth were excluded from the sample. The measurement of tooth fluorescence was carried out via computer analysis of digital images using the software ScanWhite DMC/Darwin Systems - Brazil. It was observed that dental fluorescence decreases when comparing the age groups 21-30, 31-40, 41-50 and 51-63 years. The results also showed that there is a statistically significant difference between the groups 41-50 years and 21-30 years (p=. 0.005) and also among the group 51-63 years and all other groups (p< 0.005). It can be concluded that dental fluorescence is correlated with age and has a similar and stable behavior from 7 to 20 years of age. It reaches its maximum expected value at the age of 26.5 years and thereafter decreases. © 2013 Elsevier B.V.

HTS: A new shape descriptor based on Hough Transform

In this paper we propose a novel method for shape analysis called HTS (Hough Transform Statistics), which uses statistics from Hough Transform space in order to characterize the shape of objects in digital images. Experimental results showed that the HTS descriptor is robust and presents better accuracy than some traditional shape description methods. Furthermore, HTS algorithm has linear complexity, which is an important requirement for content based image retrieval from large databases. © 2013 IEEE.

Propriedades físicas de um latossolo vermelho manejado com material orgânico e submetido à compactação

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)