Improving image classification through descriptor combination

The efficiency in image classification tasks can be improved using combined information provided by several sources, such as shape, color, and texture visual properties. Although many works proposed to combine different feature vectors, we model the descriptor combination as an optimization problem to be addressed by evolutionary-based techniques, which compute distances between samples that maximize their separability in the feature space. The robustness of the proposed technique is assessed by the Optimum-Path Forest classifier. Experiments showed that the proposed methodology can outperform individual information provided by single descriptors in well-known public datasets. © 2012 IEEE.

Measurements of simulated periodontal bone defects in inverted digital image and film-based radiograph: An in vitro study

Purpose: This study was performed to compare the inverted digital images and film-based images of dry pig mandibles to measure the periodontal bone defect depth. Materials and Methods: Forty 2-wall bone defects were made in the proximal region of the premolar in the dry pig mandibles. The digital and conventional radiographs were taken using a Schick sensor and Kodak F-speed intraoral film. Image manipulation (inversion) was performed using Adobe Photoshop 7.0 software. Four trained examiners made all of the radiographic measurements in millimeters a total of three times from the cementoenamel junction to the most apical extension of the bone loss with both types of images: inverted digital and film. The measurements were also made in dry mandibles using a periodontal probe and digital caliper. The Student's t-test was used to compare the depth measurements obtained from the two types of images and direct visual measurement in the dry mandibles. A significance level of 0.05 for a 95% confidence interval was used for each comparison. Results: There was a significant difference between depth measurements in the inverted digital images and direct visual measurements (p>|t|=0.0039), with means of 6.29 mm (IC95%:6.04-6.54) and 6.79 mm (IC95%:6.45-7.11), respectively. There was a non-significant difference between the film-based radiographs and direct visual measurements (p>|t|=0.4950), with means of 6.64mm (IC95%:6.40-6.89) and 6.79mm(IC95%:6.45-7.11), respectively. Conclusion: The periodontal bone defect measurements in the inverted digital images were inferior to film-based radiographs, underestimating the amount of bone loss. copy; 2012 by Korean Academy of Oral and Maxillofacial Radiology.

OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

Swarm-based descriptor combination and its application for image classification

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

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

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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.

Processamento digital de imagens para identificação da sigatoka negra em bananais utilizando análise de componentes principais e redes neurais artificiais

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Development of a CAD system for automatic classification of microcalcifications based on FPGA

This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.

Estimation of croplands using indicator kriging and fuzzy classification

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise da imagem digital para estimativa da área foliar em plantas de laranja Pêra

Objetivou-se, com o trabalho, avaliar dois métodos de estimativa da área foliar, em plantas de laranja Pêra, pela análise da imagem digital obtida com scanner e câmera fotográfica digital. Para determinar a área das folhas, um grupo de discos foi colocado sobre um leitor de scanner, sendo que a imagem obtida foi armazenada. Os mesmos grupos de discos foram fixados sobre cartolina branca e fotografados com câmera fotográfica digital. As imagens obtidas da câmera fotográfica e do scanner foram processadas utilizando ferramentas de um editor de imagem que permite a contagem de pixels de determinada cor, no caso verde. Para a comparação dos métodos, os discos foram submetidos a integrador óptico de área foliar modelo LICOR-3100, utilizando os mesmos agrupamentos. Foram coletadas 20 folhas (cinco em cada quadrante da planta) por parcela de um experimento para comparação de fertilizantes comerciais e doses de zinco, aplicados via foliar, em plantas de sete anos de idade. O experimento foi composto de sete tratamentos e quatro repetições, num total de 28 parcelas. Os dois métodos apresentaram alta correlação com a área estimada pelo integrador óptico de área, considerado como método de referência. O método da análise da imagem obtida com câmera fotográfica, na resolução de 5.0 megapixel, foi mais precisa quando comparada à área estimada pelo integrador óptico de área.

Estado nutricional em nitrogênio da grama esmeralda avaliado por meio do teor foliar, clorofilômetro e imagem digital, em área adubada com lodo de esgoto

A intensidade da cor verde da folha pode ser alternativa para estimar a concentração de N na planta, devido à relação entre o teor de clorofila e o de N no tecido foliar. Objetivou-se neste trabalho avaliar índices da cor verde da grama esmeralda obtidos da análise da imagem digital e pelo uso do clorofilômetro para predizer o estado nutricional em N fornecido pelo lodo de esgoto. O experimento foi instalado e desenvolvido em uma propriedade comercial de grama esmeralda, localizada na cidade de Itapetininga (SP). O delineamento experimental foi em blocos casualizados, com quatro repetições e cinco doses de lodo de esgoto: 0, 10, 20, 30 e 40 Mg ha-1, base seca. As doses de lodo aplicadas correspondem a 100, 200, 300 e 400 kg ha-1 de nitrogênio disponível. Foram avaliadas as concentrações de N e a intensidade de coloração verde da folha pelo uso do clorofilômetro (ICV) e por meio da análise da imagem digital (G, H e ICVE) aos 45, 105 e 165 dias após a aplicação do lodo. Os valores de intensidade obtidos foram correlacionados com a concentração de N na lâmina foliar e com a taxa de cobertura do solo determinada nas mesmas épocas. A aplicação de doses de lodo de esgoto proporcionou aumento dos índices de cor verde e da concentração de N nas folhas da grama esmeralda. A concentração de N na lâmina foliar pode auxiliar a adubação nitrogenada em cobertura, pois proporcionou altas correlações com a taxa de cobertura do solo. O matiz (H) obtido com a imagem digital e a intensidade de cor verde da folha (ICV) obtida com o clorofilômetro correlacionaram-se com a concentração de N e com a taxa de cobertura do solo e, dessa forma, podem servir como índices na recomendação da adubação nitrogenada.

Integração de imagem aérea de alta resolução e dados de varredura a laser na classificação de cenas urbanas para detectar regiões de via

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparison of simulated periodontal bone defect depth measured in digital radiographs in dedicated and non-dedicated software systems

Objectives: To compare simulated periodontal bone defect depth measured in digital radiographs with dedicated and non-dedicated software systems and to compare the depth measurements from each program with the measurements in dry mandibles.Methods: Forty periodontal bone defects were created at the proximal area of the first premolar in dry pig mandibles. Measurements of the defects were performed with a periodontal probe in the dry mandible. Periapical digital radiographs of the defects were recorded using the Schick sensor in a standardized exposure setting. All images were read using a Schick dedicated software system (CDR DICOM for Windows v.3.5), and three commonly available non-dedicated software systems (Vix Win 2000 v.1.2; Adobe Photoshop 7.0 and Image Tool 3.0). The defects were measured three times in each image and a consensus was reached among three examiners using the four software systems. The difference between the radiographic measurements was analysed using analysis of variance (ANOVA) and by comparing the measurements from each software system with the dry mandibles measurements using Student's t-test.Results: the mean values of the bone defects measured in the radiographs were 5.07 rum, 5.06 rum, 5.01 mm and 5.11 mm for CDR Digital Image and Communication in Medicine (DICOM) for Windows, Vix Win, Adobe Photoshop, and Image Tool, respectively, and 6.67 mm for the dry mandible. The means of the measurements performed in the four software systems were not significantly different, ANOVA (P = 0.958). A significant underestimation of defect depth was obtained when we compared the mean depths from each software system with the dry mandible measurements (t-test; P congruent to 0.000).Conclusions: the periodontal bone defect measurements in dedicated and in three non-dedicated software systems were not significantly different, but they all underestimated the measurements when compared with the measurements obtained in the dry mandibles.

An image analysis study of pit formation on Ti-6Al-4V

Metallographic techniques and digital image processing have been used to investigate heat-treated Ti-6Al-4V pitting corrosion, often used as aircraft components. LM and SEM metallography of 'as received', annealed (heating up to 800 degreesC/30 min and cooling furnace) and aged (heating up to 900 degreesC/30 min, quenching in water, heating up to 540 degreesC/240 min and again water-quenched) microstructures reveal pitting sites at primary and secondary alpha/beta interfaces. Microstructural arrangements influence and corrosive environment association on pit morphology could be demonstrated by digital image analysis and results statistical treatment. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Strategy to detect ground control in digital images

The identification of ground control on photographs or images is usually carried out by a human operator, who uses his natural skills to make interpretations. In Digital Photogrammetry, which uses techniques of digital image processing extraction of ground control can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features of object space and its homologous in the image space. A build-in self-diagnosis is also used in this method. It is based on implementation of data snooping statistic test in the process of spatial resection using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.