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.

Optimizing feature selection through binary charged system search

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 inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS 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 four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

Influência do ganho de massa corporal, induzido por dieta rica em sacarose, em parâmetros biométricos, bioquímicos e biofísicos de ratos Wistar

Pós-graduação em Ciências Fisiológicas - FOA

Sistema CIE Lab: análise computacional de fotografias

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Interações orais em língua inglesa no laboratório de multimídia com acesso à Internet

Pós-graduação em Estudos Linguísticos - IBILCE

Análise comparativa entre o sistema digital Digora e a digitalização da radiografia convencional na avaliação da densidade radiográfica do processo de reparo alveolar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo das características morfométricas de diferentes regiões do intestino delgado e índices zootécnicos em quatro linhagens de frangos de corte

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

Sistemas adesivos convencional e autocondicionante: análise micromecânica tridimensional da interface dentina-adesivo

Pós-graduação em Odontologia - FOA

Avaliação da eficiência de dois programas na eliminação de ruído para técnica de subtração

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Variabilidade das sub-populações de espermatozóides avaliados pela cinética em sistema computadorizado e combinação de sondas fluorescentes como praâmetro quantitativo do sêmen congelado de ovinos

Pós-graduação em Medicina Veterinária - FMVZ

Efeito da cafeína no desenvolvimento de Aedes aegypti (Diptera: Culicidae): o significado biológico das alterações do padrão de síntese de esterases

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Machine vision to identify broiler breeder behavior

Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.

Static Video Summarization through Optimum-Path Forest Clustering

This paper introduces the Optimum-Path Forest (OPF) classifier for static video summarization, being its results comparable to the ones obtained by some state-of-the-art video summarization techniques. The experimental section has been conducted using several image descriptors in two public datasets, followed by an analysis of OPF robustness regarding one ad-hoc parameter. Future works are guided to improve OPF effectiveness on each distinct video category.

HTS and HTSn: New shape descriptors based on Hough transform statistics

With the widespread proliferation of computers, many human activities entail the use of automatic image analysis. The basic features used for image analysis include color, texture, and shape. In this paper, we propose a new shape description method, called Hough Transform Statistics (HTS), which uses statistics from the Hough space to characterize the shape of objects or regions in digital images. A modified version of this method, called Hough Transform Statistics neighborhood (HTSn), is also presented. Experiments carried out on three popular public image databases showed that the HTS and HTSn descriptors are robust, since they presented precision-recall results much better than several other well-known shape description methods. When compared to Beam Angle Statistics (BAS) method, a shape description method that inspired their development, both the HTS and the HTSn methods presented inferior results regarding the precision-recall criterion, but superior results in the processing time and multiscale separability criteria. The linear complexity of the HTS and the HTSn algorithms, in contrast to BAS, make them more appropriate for shape analysis in high-resolution image retrieval tasks when very large databases are used, which are very common nowadays. (C) 2014 Elsevier Inc. All rights reserved.

Reconhecimento de contorno de edifício em imagens de alta resolução usando os momentos complexos de Zernike

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