Characterization of texture in image of skin lesions by support vector machine

Due to the increased incidence of skin cancer, computational methods based on intelligent approaches have been developed to aid dermatologists in the diagnosis of skin lesions. This paper proposes a method to classify texture in images, since it is an important feature for the successfully identification of skin lesions. For this is defined a feature vector, with the fractal dimension of images through the box-counting method (BCM), which is used with a SVM to classify the texture of the lesions in to non-irregular or irregular. With the proposed solution, we could obtain an accuracy of 72.84%. © 2012 AISTI.

Automatic segmentation of latent fingerprints

Latent fingerprints are routinely found at crime scenes due to the inadvertent contact of the criminals' finger tips with various objects. As such, they have been used as crucial evidence for identifying and convicting criminals by law enforcement agencies. However, compared to plain and rolled prints, latent fingerprints usually have poor quality of ridge impressions with small fingerprint area, and contain large overlap between the foreground area (friction ridge pattern) and structured or random noise in the background. Accordingly, latent fingerprint segmentation is a difficult problem. In this paper, we propose a latent fingerprint segmentation algorithm whose goal is to separate the fingerprint region (region of interest) from background. Our algorithm utilizes both ridge orientation and frequency features. The orientation tensor is used to obtain the symmetric patterns of fingerprint ridge orientation, and local Fourier analysis method is used to estimate the local ridge frequency of the latent fingerprint. Candidate fingerprint (foreground) regions are obtained for each feature type; an intersection of regions from orientation and frequency features localizes the true latent fingerprint regions. To verify the viability of the proposed segmentation algorithm, we evaluated the segmentation results in two aspects: a comparison with the ground truth foreground and matching performance based on segmented region. © 2012 IEEE.

Heterogeneous demand and market segmentation: the Argentine pension funds system

Includes bibliography

Unsupervised segmentation method for cuboidal cell nuclei in histological prostate images based on minimum cross entropy

This paper presents a novel segmentation method for cuboidal cell nuclei in images of prostate tissue stained with hematoxylin and eosin. The proposed method allows segmenting normal, hyperplastic and cancerous prostate images in three steps: pre-processing, segmentation of cuboidal cell nuclei and post-processing. The pre-processing step consists of applying contrast stretching to the red (R) channel to highlight the contrast of cuboidal cell nuclei. The aim of the second step is to apply global thresholding based on minimum cross entropy to generate a binary image with candidate regions for cuboidal cell nuclei. In the post-processing step, false positives are removed using the connected component method. The proposed segmentation method was applied to an image bank with 105 samples and measures of sensitivity, specificity and accuracy were compared with those provided by other segmentation approaches available in the specialized literature. The results are promising and demonstrate that the proposed method allows the segmentation of cuboidal cell nuclei with a mean accuracy of 97%. © 2013 Elsevier Ltd. All rights reserved.

Automatic segmentation and classification of human intestinal parasites from microscopy images

Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

Texture profile and correlation between sensory and instrumental analyses on extruded snacks

Instrumental texture analysis on extruded snacks is widely applied, however there is no scientific consensus about the test and probe types that can be correlated with the sensory texture of snacks. Eleven commercial extruded snacks of different shapes were evaluated instrumentally using different probes and sensorially through descriptive analysis. The snack texture was described using the attributes of hardness, crispness, adhesiveness, fracturability and chewiness. Cylindrical snacks were described through crispness and fracturability, pelleted and shell-shaped snacks by chewiness and ring-shaped snacks by adhesiveness and hardness. Hardness and adhesiveness were correlated with a Warner-Bratzler test using a V shape probe (r = 0.718 and r = 0.763, respectively), while fracturability and chewiness were correlated with a Warner-Bratzler test using a guillotine (r = 0.776 and r = 0.662, respectively). The fairly strong good correlations enable application of these instrumental tests as an indication of the sensory texture of extruded snacks. © 2013 Elsevier Ltd. All rights reserved.

Combining anisotropic diffusion, transport equation and texture synthesis for inpainting textured images

In this work we propose a new image inpainting technique that combines texture synthesis, anisotropic diffusion, transport equation and a new sampling mechanism designed to alleviate the computational burden of the inpainting process. Given an image to be inpainted, anisotropic diffusion is initially applied to generate a cartoon image. A block-based inpainting approach is then applied so that to combine the cartoon image and a measure based on transport equation that dictates the priority on which pixels are filled. A sampling region is then defined dynamically so as to hold the propagation of the edges towards image structures while avoiding unnecessary searches during the completion process. Finally, a cartoon-based metric is computed to measure likeness between target and candidate blocks. Experimental results and comparisons against existing techniques attest the good performance and flexibility of our technique when dealing with real and synthetic images. © 2013 Elsevier B.V. All rights reserved.

Motherhood wage penalties and labour market segmentation: Evidence from Argentina

Includes bibliography.

Método de detecção e classificação de lesões de pele em imagens digitais a partir do modelo Chan-Vese e máquina de vetor de suporte

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Informality and labour market segmentation: the case of Argentina

The document evaluates the presence of segmentation in the Argentinean labour market. The analysis is centred on the comparison of the earnings of formal and informal workers. Two different approaches to the definition of informality are used. The existence of a formal premium is tested using dynamic data and semiparametric techniques. The period analysed is 1996-2006 for all urban surveyed areas. Our results support the segmentation hypothesis for the Argentine urban labour market: workers with similar probabilities of entering/exiting across sectors obtain different earnings.

Uma abordagem híbrida e semiautomática para estimativa de regiões cobertas por nuvens e sombras em imagens de satélite: análise e avaliação

Os principais objetivos deste trabalho são propor um algoritmo eficiente e o mais automático possível para estimar o que está coberto por regiões de nuvens e sombras em imagens de satélite; e um índice de confiabilidade, que seja aplicado previamente à imagem, visando medir a viabilidade da estimação das regiões cobertas pelos componentes atmosféricos usando tal algoritmo. A motivação vem dos problemas causados por esses elementos, entre eles: dificultam a identificação de objetos de imagem, prejudicam o monitoramento urbano e ambiental, e desfavorecem etapas cruciais do processamento digital de imagens para extrair informações ao usuário, como segmentação e classificação. Através de uma abordagem híbrida, é proposto um método para decompor regiões usando um filtro passa-baixas não-linear de mediana, a fim de mapear as regiões de estrutura (homogêneas), como vegetação, e de textura (heterogêneas), como áreas urbanas, na imagem. Nessas áreas, foram aplicados os métodos de restauração Inpainting por suavização baseado em Transformada Cosseno Discreta (DCT), e Síntese de Textura baseada em modelos, respectivamente. É importante salientar que as técnicas foram modificadas para serem capazes de trabalhar com imagens de características peculiares que são obtidas por meio de sensores de satélite, como por exemplo, as grandes dimensões e a alta variação espectral. Já o índice de confiabilidade, tem como objetivo analisar a imagem que contém as interferências atmosféricas e daí estimar o quão confiável será a redefinição com base no percentual de cobertura de nuvens sobre as regiões de textura e estrutura. Tal índice é composto pela combinação do resultado de algoritmos supervisionados e não-supervisionados envolvendo 3 métricas: Exatidão Global Média (EGM), Medida De Similaridade Estrutural (SSIM) e Confiança Média Dos Pixels (CM). Finalmente, verificou-se a eficácia destas metodologias através de uma avaliação quantitativa (proporcionada pelo índice) e qualitativa (pelas imagens resultantes do processamento), mostrando ser possível a aplicação das técnicas para solucionar os problemas que motivaram a realização deste trabalho.

Leaching potential and residual effect of amicarbazone in soils of contrasting texture

The infestation of weeds is a major biotic factor in the agroecosystem of cane sugar that may interfere in development and crop productivity. This study aimed to evaluate the potential for leaching and residual effects of the herbicide amicarbazone in contrasting soils. Samples were Quartzarenic Neosol (NR - sandy texture) and Red Latosol (LR - clay texture). For the leaching potential, after application of herbicide amicarbazone (NR 1.05 kg ha(-1) and LR 1.40 kg ha(-1)), layers of 0, 20, 40, 60, 80 and 100 mm of water were applied to soil columns. We evaluated the residual effect after the permanence of the herbicide in soil of clay texture and sandy for periods of 0, 25, 50, 75 and 100 days after application (DAA) of amicarbazone (0, 1.05, 1.40 kg ha(-1)) treatments. The amicarbazone started showing high leaching from the 60 mm layer of water in sandy texture soils, evidencing a shorter residual effect. In clay soil, slides from 20 to 80 mm of water reduced the biomass until a depth of 5-10 cm, with the use of this herbicide. Based on these results, we conclude that the amicarbazone showed higher leaching and lower residual effects in sandy soil. The residual effect of amicarbazone was prolonged as the content of clay and organic matter present in the soil increased.

Application of two segmentation protocols during the processing of virtual images in rapid prototyping: ex vivo study with human dry mandibles

The aim of this study was to evaluate the accuracy of virtual three-dimensional (3D) reconstructions of human dry mandibles, produced from two segmentation protocols (outline only and all-boundary lines).Twenty virtual three-dimensional (3D) images were built from computed tomography exam (CT) of 10 dry mandibles, in which linear measurements between anatomical landmarks were obtained and compared to an error probability of 5 %.The results showed no statistically significant difference among the dry mandibles and the virtual 3D reconstructions produced from segmentation protocols tested (p = 0,24).During the designing of a virtual 3D reconstruction, both outline only and all-boundary lines segmentation protocols can be used.Virtual processing of CT images is the most complex stage during the manufacture of the biomodel. Establishing a better protocol during this phase allows the construction of a biomodel with characteristics that are closer to the original anatomical structures. This is essential to ensure a correct preoperative planning and a suitable treatment.

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)