SUMMARYFace recognition plays an important role in security applications, but in real-world conditions face images are typically subject to issues that compromise recognition performance, such as geometric transformations, occlusions and changes in illumination. Most face detection and recognition works to date deal with single face images using global features and supervised learning. Differently from that context, here we propose a multiple face recognition approach based on local features which does not rely on supervised learning. In order to deal with multiple face images under varying conditions, the extraction of invariant and discriminative local features is achieved by using the SURF (Speeded-Up Robust Features) approach, and the search for regions from which optimal features can be extracted is done by an improved ABC (Artificial Bee Colony) algorithm. Thresholds and parameters for SURF and improved ABC algorithms are determined experimentally. The approach was extensively assessed on 99 different still images -more than 400 trials were conducted using 20 target face images and still images under different acquisition conditions. Results show that our approach is promising for real-world face recognition applications concerning different acquisition conditions and transformations.

<p> <span style="font-size:10.0pt;">Objectives: The overall aim is to propose a general framework to build any kind of interactive digital atlas. It can be used either as pedagogical support to study human anatomy or as a tool to aid health professionals improving the quality of the human resources formation. Methods: To illustrate the use of the proposed methodology was build an atlas of intracranial human anatomy. We used 3D surface rendering techniques to create a brain atlas that would allow us to correlate bi-dimensional MRI images with 3D brain structures. Results: The system was coded in Java and distributed under GNU/GLP license, making it available to use and/or to expand and serve as an educational tool allow medical students to use it to evaluate the special relationships among structures. Conclusions: The characteristics of the obtained Atlas are essential in the Brazilian public health context, where professionals in several different geographical locations (submitted to distinct informatics infrastructure) need to be trained. </span> </p>

Este trabalho apresenta um novo conjunto de transformações de imagens que podem ser utilizadas como uma etapa adicional em diversas aplicações, tal como segmentação, de modo a evitar o uso de operações com custo computacional mais alto. Tais transformações utilizam como base operações de morfologia matemática e possuem a forma de um operador do tipo toggle. Inicialmente, foi definida uma nova operação com propriedades espaço-escala, através da qual pode-se obter uma simplificação bem controlada da imagem em que máximos e mínimos interagem ao mesmo tempo, uma vantagem em relação a outras abordagens que consideram transformações de extremos separadamente. A análise de diferentes níveis de representação traz inúmeras vantagens, possibilitando lidar adequadamente com a natureza multi-escala das images e permitindo a extração das características específicas que se tornam explícitas a cada escala. A partir de variações na formulação e na forma de aplicação do operador proposto, foi possível definir uma nova operação de limiarização adaptativa multi-escala e um método de filtragem de ruído. Foram realizados diversos experimentos que comprovaram as vantagens da utilização das abordagens propostas. vii

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