ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, 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 image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics 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 segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

New trends in musical genre classification using optimum-path forest

Musical genre classification has been paramount in the last years, mainly in large multimedia datasets, in which new songs and genres can be added at every moment by anyone. In this context, we have seen the growing of musical recommendation systems, which can improve the benefits for several applications, such as social networks and collective musical libraries. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for musical genre classification, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster for some applications. Experiments in two public datasets were conducted against Support Vector Machines and a Bayesian classifier to show the validity of our work. In addition, we have executed an experiment using very recent hybrid feature selection techniques based on OPF to speed up feature extraction process. © 2011 International Society for Music Information Retrieval.

Automatic classification of fish germ cells through optimum-path forest

The spermatogenesis is crucial to the species reproduction, and its monitoring may shed light over some important information of such process. Thus, the germ cells quantification can provide useful tools to improve the reproduction cycle. In this paper, we present the first work that address this problem in fishes with machine learning techniques. We show here how to obtain high recognition accuracies in order to identify fish germ cells with several state-of-the-art supervised pattern recognition techniques. © 2011 IEEE.

Evaluation epidermal p53 immunostaining by digital image analysis

Digital techniques have been developed and validated to assess semiquantitatively immunohistochemical nuclear staining. Currently visual classification is the standard for qualitative nuclear evaluation. Analysis of pixels that represents the immunohistochemical labeling can be more sensitive, reproducible and objective than visual grading. This study compared two semiquantitative techniques of digital image analysis with three techniques of visual analysis imaging to estimate the p53 nuclear immunostaining. Methods: Sixty-three sun-exposed forearm-skin biopsies were photographed and submitted to three visual analyses of images: the qualitative visual evaluation method (0 to 4 +), the percentage of labeled nuclei and HSCORE. Digital image analysis was performed using ImageJ 1.45p; the density of nuclei was scored per ephitelial area (DensNU) and the pixel density was established in marked suprabasal epithelium (DensPSB). Results: Statistical significance was found in: the agreement and correlation among the visual estimates of evaluators, correlation among the median visual score of the evaluators, the HSCORE and the percentage of marked nuclei with the DensNU and DensPSB estimates. DensNU was strongly correlated to the percentage of p53-marked nuclei in the epidermis, and DensPSB with the HSCORE. Conclusion: The parameters presented herein can be applied in routine analysis of immunohistochemical nuclear staining of epidermis. © 2012 John Wiley & Sons A/S.

Signal classification of submerged aquatic vegetation based on the hemispherical-conical reflectance factor spectrum shape in the yellow and red regions

The water column overlying the submerged aquatic vegetation (SAV) canopy presents difficulties when using remote sensing images for mapping such vegetation. Inherent and apparent water optical properties and its optically active components, which are commonly present in natural waters, in addition to the water column height over the canopy, and plant characteristics are some of the factors that affect the signal from SAV mainly due to its strong energy absorption in the near-infrared. By considering these interferences, a hypothesis was developed that the vegetation signal is better conserved and less absorbed by the water column in certain intervals of the visible region of the spectrum; as a consequence, it is possible to distinguish the SAV signal. To distinguish the signal from SAV, two types of classification approaches were selected. Both of these methods consider the hemispherical-conical reflectance factor (HCRF) spectrum shape, although one type was supervised and the other one was not. The first method adopts cluster analysis and uses the parameters of the band (absorption, asymmetry, height and width) obtained by continuum removal as the input of the classification. The spectral angle mapper (SAM) was adopted as the supervised classification approach. Both approaches tested different wavelength intervals in the visible and near-infrared spectra. It was demonstrated that the 585 to 685-nm interval, corresponding to the green, yellow and red wavelength bands, offered the best results in both classification approaches. However, SAM classification showed better results relative to cluster analysis and correctly separated all spectral curves with or without SAV. Based on this research, it can be concluded that it is possible to discriminate areas with and without SAV using remote sensing. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Ki-67 labeling in canine perianal glands neoplasms: A novel approach for immunohistological diagnostic and prognostic

Background: The antibody Ki-67 is a reliable and easy tool to accurately assess the growth fraction of neoplasms in humans and animals, and it has been used to predict the clinical outcome. Therefore, the aim of the present study was to investigate the immunohistochemical expression pattern of Ki-67 in normal and neoplastic perianal glands of dogs to evaluate the possible use of this proliferation marker as an ancillary method of perianal tumor diagnosis. We studied 42 cases of perianal gland neoplasms including adenomas (n = 15), epitheliomas (n = 15), and carcinomas (n = 12). As controls, 13 tissue samples from normal perianal glands were used. A Ki-67 index was established by a computer-assisted image analysis and compared with manual counting. Results: Out of the 42 cases of perianal gland neoplasms, 34 were from males and eight from females. Recurrence was reported in 14 cases, being higher (8/12) in carcinomas. Immunostaining for Ki-67 revealed that the carcinomas showed a higher proliferation rate (9.87%) compared to groups of epitheliomas (2.66%) and adenomas (0.36%). For adenomas and epitheliomas of the perianal glands the computer-assisted counting and the manual counting gave similar results; however, only the computer-assisted image analysis was efficient to predict the perianal gland carcinoma recurrence.Conclusion: Since there were significant differences in the number of Ki-67-positive nuclei, this marker proved to be effective in helping the classification of perianal gland neoplasms and to refine the diagnosis criteria, especially in those samples with high variation in morphology/area. Also, higher Ki-67 index is related to recurrence in cases of perianal gland carcinomas. Further, the computer-assisted image analysis proved to be a fast and reliable method to assess the Ki-67 index in perianal gland neoplasms. © 2013 Pereira et al.; licensee BioMed Central Ltd.

ECG arrhythmia classification based on optimum-path forest

An important tool for the heart disease diagnosis is the analysis of electrocardiogram (ECG) signals, since the non-invasive nature and simplicity of the ECG exam. According to the application, ECG data analysis consists of steps such as preprocessing, segmentation, feature extraction and classification aiming to detect cardiac arrhythmias (i.e.; cardiac rhythm abnormalities). Aiming to made a fast and accurate cardiac arrhythmia signal classification process, we apply and analyze a recent and robust supervised graph-based pattern recognition technique, the optimum-path forest (OPF) classifier. To the best of our knowledge, it is the first time that OPF classifier is used to the ECG heartbeat signal classification task. We then compare the performance (in terms of training and testing time, accuracy, specificity, and sensitivity) of the OPF classifier to the ones of other three well-known expert system classifiers, i.e.; support vector machine (SVM), Bayesian and multilayer artificial neural network (MLP), using features extracted from six main approaches considered in literature for ECG arrhythmia analysis. In our experiments, we use the MIT-BIH Arrhythmia Database and the evaluation protocol recommended by The Association for the Advancement of Medical Instrumentation. A discussion on the obtained results shows that OPF classifier presents a robust performance, i.e.; there is no need for parameter setup, as well as a high accuracy at an extremely low computational cost. Moreover, in average, the OPF classifier yielded greater performance than the MLP and SVM classifiers in terms of classification time and accuracy, and to produce quite similar performance to the Bayesian classifier, showing to be a promising technique for ECG signal analysis. © 2012 Elsevier Ltd. All rights reserved.

Topological K-classification of finitely determined map germs

We consider smooth finitely C 0-K-determined map germs f: (ℝn, 0) → (ℝp, 0) and we look at the classification under C 0-K-equivalence. The main tool is the homotopy type of the link, which is obtained by intersecting the image of f with a small enough sphere centered at the origin. When f -1(0) = {0}, the link is a smooth map between spheres and f is C 0-K-equivalent to the cone of its link. When f -1(0) ≠ {0}, we consider a link diagram, which contains some extra information, but again f is C 0-K-equivalent to the generalized cone. As a consequence, we deduce some known results due to Nishimura (for n = p) or the first named author (for n < p). We also prove some new results of the same nature. © 2012 Springer Science+Business Media Dordrecht.

Caracterização citogenética de populações de crisopídeos (Neuroptera: Chrysopidae) de ocorrência em Jaboticabal, SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Classificação de cobertura do solo utilizando árvores de decisão e sensoriamento remoto

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Dinâmica no uso da terra de 1991 a 2010 da região semiárida do estado do Piauí: cajucultura e apicultura

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Cephalometric evaluation of the predictability of bimaxillary surgical-orthodontic treatment outcomes in long face pattern patients: a retrospective study

OBJECTIVE: The aim of this study was to compare by means of McNamara as well as Legan and Burstone's cephalometric analyses, both manual and digitized (by Dentofacial Planner Plus and Dolphin Image software) prediction tracings to post-surgical results. METHODS: Pre and post-surgical teleradiographs (6 months) of 25 long face patients subjected to combined orthognathic surgery were selected. Manual and computerized prediction tracings of each patient were performed and cephalometrically compared to post-surgical outcomes. This protocol was repeated in order to evaluate the method error and statistical evaluation was conducted by means of analysis of variance and Tukey's test. RESULTS: A higher frequency of cephalometric variables, which were not statistically different from the actual post-surgical results for the manual method, was observed. It was followed by DFPlus and Dolphin software; in which similar cephalometric values for most variables were observed. CONCLUSION: It was concluded that the manual method seemed more reliable, although the predictability of the evaluated methods (computerized and manual) proved to be reasonably satisfactory and similar.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Nature-Inspired Framework for Hyperspectral Band Selection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)