Sistema auxiliar na análise de mamogramas digitais

This work proposes the development of a Computer System for Analysis of Mammograms SCAM, that aids the doctor specialist in the identification and analysis of existent lesions in digital mammograms. The computer system for digital mammograms processing will make use of a group of techniques of Digital Image Processing (DIP), with the purpose of aiding the medical professional to extract the information contained in the mammogram. This system possesses an interface of easy use for the user, allowing, starting from the supplied mammogram, a group of processing operations, such as, the enrich of the images through filtering techniques, the segmentation of areas of the mammogram, the calculation the area of the lesions, thresholding the lesion, and other important tools for the medical professional's diagnosis. The Wavelet Transform will used and integrated into the computer system, with the objective of allowing a multiresolution analysis, thus supplying a method for identifying and analyzing microcalcifications

Compressão Seletiva de Imagens Coloridas com Detecção Automática de Regiões de Interesse

There has been an increasing tendency on the use of selective image compression, since several applications make use of digital images and the loss of information in certain regions is not allowed in some cases. However, there are applications in which these images are captured and stored automatically making it impossible to the user to select the regions of interest to be compressed in a lossless manner. A possible solution for this matter would be the automatic selection of these regions, a very difficult problem to solve in general cases. Nevertheless, it is possible to use intelligent techniques to detect these regions in specific cases. This work proposes a selective color image compression method in which regions of interest, previously chosen, are compressed in a lossless manner. This method uses the wavelet transform to decorrelate the pixels of the image, competitive neural network to make a vectorial quantization, mathematical morphology, and Huffman adaptive coding. There are two options for automatic detection in addition to the manual one: a method of texture segmentation, in which the highest frequency texture is selected to be the region of interest, and a new face detection method where the region of the face will be lossless compressed. The results show that both can be successfully used with the compression method, giving the map of the region of interest as an input

The influence of visual inter-hemispheric connections on spiking, assembly and LFP activities, and their phase relationship during figure-ground stimulation

Desde os descobrimentos pioneiros de Hubel e Wiesel acumulou-se uma vasta literatura descrevendo as respostas neuronais do córtex visual primário (V1) a diferentes estímulos visuais. Estes estímulos consistem principalmente em barras em movimento, pontos ou grades, que são úteis para explorar as respostas dentro do campo receptivo clássico (CRF do inglês classical receptive field) a características básicas dos estímulos visuais como a orientação, direção de movimento, contraste, entre outras. Entretanto, nas últimas duas décadas, tornou-se cada vez mais evidente que a atividade de neurônios em V1 pode ser modulada por estímulos fora do CRF. Desta forma, áreas visuais primárias poderiam estar envolvidas em funções visuais mais complexas como, por exemplo, a separação de um objeto ou figura do seu fundo (segregação figura-fundo) e assume-se que as conexões intrínsecas de longo alcance em V1, assim como as conexões de áreas visuais superiores, estão ativamente envolvidas neste processo. Sua possível função foi inferida a partir da análise das variações das respostas induzidas por um estímulo localizado fora do CRF de neurônios individuais. Mesmo sendo muito provável que estas conexões tenham também um impacto tanto na atividade conjunta de neurônios envolvidos no processamento da figura quanto no potencial de campo, estas questões permanecem pouco estudadas. Visando examinar a modulação do contexto visual nessas atividades, coletamos potenciais de ação e potenciais de campo em paralelo de até 48 eletrodos implantados na área visual primária de gatos anestesiados. Estimulamos com grades compostas e cenas naturais, focando-nos na atividade de neurônios cujo CRF estava situado na figura. Da mesma forma, visando examinar a influência das conexões laterais, o sinal proveniente da área visual isotópica e contralateral foi removido através da desativação reversível por resfriamento. Fizemos isso devido a: i) as conexões laterais intrínsecas não podem ser facilmente manipuladas sem afetar diretamente os sinais que estão sendo medidos, ii) as conexões inter-hemisféricas compartilham as principais características anatômicas com a rede lateral intrínseca e podem ser vistas como uma continuação funcional das mesmas entre os dois hemisférios e iii) o resfriamento desativa as conexões de forma causal e reversível, silenciando temporariamente seu sinal, permitindo conclusões diretas a respeito da sua contribuição. Nossos resultados demonstram que o mecanismo de segmentação figurafundo se reflete nas taxas de disparo de neurônios individuais, assim como na potência do potencial de campo e na relação entre sua fase e os padrões de disparo produzidos pela população. Além disso, as conexões laterais inter-hemisféricas modulam estas variáveis dependendo da estimulação feita fora do CRF. Observamos também uma influência deste circuito lateral na coerência entre potenciais de campo entre eletrodos distantes. Em conclusão, nossos resultados dão suporte à ideia de um mecanismo complexo de segmentação figura-fundo atuando desde as áreas visuais primárias em diferentes escalas de frequência. Esse mecanismo parece envolver grupos de neurônios ativos sincronicamente e dependentes da fase do potencial de campo. Nossos resultados também são compatíveis com a hipótese que conexões laterais de longo alcance também fazem parte deste mecanismo

Segmentação Fuzzy de Texturas e Vídeos

The segmentation of an image aims to subdivide it into constituent regions or objects that have some relevant semantic content. This subdivision can also be applied to videos. However, in these cases, the objects appear in various frames that compose the videos. The task of segmenting an image becomes more complex when they are composed of objects that are defined by textural features, where the color information alone is not a good descriptor of the image. Fuzzy Segmentation is a region-growing segmentation algorithm that uses affinity functions in order to assign to each element in an image a grade of membership for each object (between 0 and 1). This work presents a modification of the Fuzzy Segmentation algorithm, for the purpose of improving the temporal and spatial complexity. The algorithm was adapted to segmenting color videos, treating them as 3D volume. In order to perform segmentation in videos, conventional color model or a hybrid model obtained by a method for choosing the best channels were used. The Fuzzy Segmentation algorithm was also applied to texture segmentation by using adaptive affinity functions defined for each object texture. Two types of affinity functions were used, one defined using the normal (or Gaussian) probability distribution and the other using the Skew Divergence. This latter, a Kullback-Leibler Divergence variation, is a measure of the difference between two probability distributions. Finally, the algorithm was tested in somes videos and also in texture mosaic images composed by images of the Brodatz album

Renderizações não fotorealísticas para estilização de imagens e vídeos usando areia colorida

Non-Photorealisitc Rendering (NPR) is a class of techniques that aims to reproduce artistic techniques, trying to express feelings and moods on the rendered scenes, giving an aspect of that they had been made "by hand". Another way of defining NPR is that it is the processing of scenes, images or videos into artwork, generating scenes, images or videos that can have the visual appeal of pieces of art, expressing the visual and emotional characteristics of artistic styles. This dissertation presents a new method of NPR for stylization of images and videos, based on a typical artistic expression of the Northeast region of Brazil, that uses colored sand to compose landscape images on the inner surface of glass bottles. This method is comprised by one technique for generating 2D procedural textures of sand, and two techniques that mimic effects created by the artists using their tools. It also presents a method for generating 21 2D animations in sandbox from the stylized video. The temporal coherence within these stylized videos can be enforced on individual objects with the aid of a video segmentation algorithm. The present techniques in this work were used on stylization of synthetic and real videos, something close to impossible to be produced by artist in real life

Segmentação fuzzy de imagens coloridas com características texturais: uma aplicação a rochas sedimentares

Image segmentation is the process of labeling pixels on di erent objects, an important step in many image processing systems. This work proposes a clustering method for the segmentation of color digital images with textural features. This is done by reducing the dimensionality of histograms of color images and using the Skew Divergence to calculate the fuzzy a nity functions. This approach is appropriate for segmenting images that have colorful textural features such as geological, dermoscopic and other natural images, as images containing mountains, grass or forests. Furthermore, experimental results of colored texture clustering using images of aquifers' sedimentary porous rocks are presented and analyzed in terms of precision to verify its e ectiveness.