Incorporation of soybean by-product okara and inulin in a probiotic soy yoghurt: texture profile and sensory acceptance

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

Effect of octenyl succinylated waxy starch as a fat mimetic on texture, microstructure and physicochemical properties of Minas fresh cheese

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comparative analysis of two techniques for detection and segmentation of moving bodies

This paper makes a comparative analysis of results produced by the application of two techniques for the detection and segmentation of bodies in motion captured in images sequence, namely: 1) technique based on the temporal average of the values of each pixel recorded in N consecutive image frames and, 2) technique based on historical values associated with pixels recorded in different frames of an image sequence.

An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

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

Segmentation of Scanning Electron Microscopy Images From Natural Rubber Samples With Gold Nanoparticles Using Starlet Wavelets

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

Estimating the concentration of gold nanoparticles incorporated on natural rubber membranes using multi-level starlet optimal segmentation

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

Optimum-Path Forest Applied for Breast Masses Classification

In Computer-Aided Diagnosis-based schemes in mammography analysis each module is interconnected, which directly affects the system operation as a whole. The identification of mammograms with and without masses is highly needed to reduce the false positive rates regarding the automatic selection of regions of interest for further image segmentation. This study aims to evaluate the performance of three techniques in classifying regions of interest as containing masses or without masses (without clinical findings), as well as the main contribution of this work is to introduce the Optimum-Path Forest (OPF) classifier in this context, which has never been done so far. Thus, we have compared OPF against with two sorts of neural networks in a private dataset composed by 120 images: Radial Basis Function and Multilayer Perceptron (MLP). Texture features have been used for such purpose, and the experiments have demonstrated that MLP networks have been slightly better than OPF, but the former is much faster, which can be a suitable tool for real-time recognition systems.

Algorithms for automatic segmentation of bovine embryos produced

In vitro production has been employed in bovine embryos and quantification of lipids is fundamental to understand the metabolism of these embryos. This paper presents a unsupervised segmentation method for histological images of bovine embryos. In this method, the anisotropic filter was used in the differents RGB components. After pre-processing step, the thresholding technique based on maximum entropy was applied to separate lipid droplets in the histological slides in different stages: early cleavage, morula and blastocyst. In the postprocessing step, false positives are removed using the connected components technique that identify regions with excess of dye near pellucid zone. The proposed segmentation method was applied in 30 histological images of bovine embryos. Experiments were performed with the images and statistical measures of sensitivity, specificity and accuracy were calculated based on reference images (gold standard). The value of accuracy of the proposed method was 96% with standard deviation of 3%.

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

Segmentation of Cell Nuclei Regions in Epithelium of Prostate Glands

This paper proposes a method for segmentation of cell nuclei regions in epithelium of prostate glands. This structure provides information to diagnosis and prognosis of prostate cancer. In the initial step, the contrast stretching technique was applied in image in order to improve the contrast between regions of interest and other regions. After, the global thresholding technique was applied and the value of threshold was defined empirically. Finally, the false positive regions were removed using the connected components technique. The performance of the proposed method was compared with the Otsu technique and statistical measures of accuracy were calculated based on reference images (gold standard). The result of the mean value of accuracy of proposed method was 93% ± 0.07.

Changes in nuclear morphology and chromatin texture of basal keratinocytes in melasma

BackgroundThe pathogenesis of melasma and the role of keratinocytes in disease development and maintenance are not completely understood. Dermal abnormalities, the expression of inflammatory mediators, growth factors, epithelial expression of melanocortin and sexual hormones receptors suggest that not only melanocytes, but entire epidermal melanin unit is involved in melasma physiopathology.ObjectivesTo compare nuclear morphological features and chromatin texture between basal keratinocytes in facial melasma and adjacent normal skin.MethodsWe took facial skin biopsies (2mm melasma and adjacent normal skin) from women processed for haematoxylin and eosin. Thirty non-overlapping basal keratinocyte nuclei were segmented and descriptors of area, highest diameter, perimeter, circularity, pixel intensity, profilometric index (Ra) and fractal dimension were extracted using ImageJ software.ResultsBasal keratinocyte nuclei from facial melasma epidermis displayed larger size, irregular shape, hyperpigmentation and chromatin heterogeneity by fractal dimension than perilesional skin.ConclusionBasal keratinocytes from facial melasma display changes in nuclear form and chromatin texture, suggesting that the phenotype differences between melasma and adjacent facial skin can result from complete epidermal melanin unit alterations, not just hypertrophic melanocytes.

Effect of the addition of wheat fiber and partial pork back fat on the chemical composition, texture and sensory property of low-fat bologna sausage containing inulin and oat fiber

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Available nitrogen and responses to nitrogen fertilizer in brazilian eucalypt plantations on soils of contrasting texture

Eucalyptus plantations have seldom responded to N fertilization in tropical and subtropical regions of Brazil. This implies that rates of N mineralization have been adequate to supply tree needs. However, subsequent crop rotations with low N fertilization may result in declining concentrations of organic and potentially mineralizable N (N-0), and consequent loss of wood productivity. This study investigated (a) in situ N mineralization and N-0 in soils of eucalypt plantations in Sao Paulo state, Brazil; (b) tree growth responses to N fertilizer applied 6-18 months after planting; and (c) the relationships between N-0,N- other soil attributes and tree growth. We established eleven N fertilizer trials (maximum 240 kg ha(-1) of N) in E. grandis and E. grandis x urophylla plantations. The soil types at most sites were Oxisols and Quartzipsamments, with a range of organic matter (18 to 55 g kg(-1)) and clay contents (8% to 67%) in the 0-20 cm layer. Concentrations of N-0 were measured using anaerobic incubation on soil samples collected every three months (different seasons). The samples collected in spring and summer had N-0 140-400 kg ha(-1) (10%-19% total soil N), which were best correlated with soil texture and organic matter content. Rates of in situ net N mineralization (0-20 cm) ranged from 100 to 200 kg ha(-1) year(-1) and were not correlated with clay, total N, or N-0. These high N mineralization rates resulted in a low response to N fertilizer application during the early ages of stand growth, which were highest on sandy soils. At the end of the crop rotation, the response to N fertilizer was negligible and non-significant at all sites.

Statistical analysis of texture in trunk images for biometric identification of tree species

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

Image segmentation through combined methods: watershed transform, unsupervised distance learning and normalized cut

Research on image processing has shown that combining segmentation methods may lead to a solid approach to extract semantic information from different sort of images. Within this context, the Normalized Cut (NCut) is usually used as a final partitioning tool for graphs modeled in some chosen method. This work explores the Watershed Transform as a modeling tool, using different criteria of the hierarchical Watershed to convert an image into an adjacency graph. The Watershed is combined with an unsupervised distance learning step that redistributes the graph weights and redefines the Similarity matrix, before the final segmentation step using NCut. Adopting the Berkeley Segmentation Data Set and Benchmark as a background, our goal is to compare the results obtained for this method with previous work to validate its performance.