Resumo em Inglês:

A critical issue of applying Linear Discriminant Analysis (LDA) is both the singularity and instability of the within-class scatter matrix. In practice, particularly in image recognition applications such as face recognition, there are often a large number of pixels or pre-processed features available, but the total number of training patterns is limited and commonly less than the dimension of the feature space. In this study, a new LDA-based method is proposed. It is based on a straightforward stabilisation approach for the within-class scatter matrix. In order to evaluate its effectiveness, experiments on face recognition using the well-known ORL and FERET face databases were carried out and compared with other LDA-based methods. The classification results indicate that our method improves the LDA classification performance when the within-class scatter matrix is not only singular but also poorly estimated, with or without a Principal Component Analysis intermediate step and using less linear discriminant features. Since statistical discrimination methods are suitable not only for classification but also for characterisation of differences between groups of patterns, further experiments were carried out in order to extend the new LDA-based method to visually analyse the most discriminating hyper-plane separating two populations. The additional results based on frontal face images indicate that the new LDA-based mapping provides an intuitive interpretation of the two-group classification tasks performed, highlighting the group differences captured by the multivariate statistical approach proposed.

Resumo em Inglês:

This paper describes an accurate method for computing the dimensions of boxes directly from perspective projection images acquired by conventional cameras. The approach is based on projective geometry and computes the box dimensions using data extracted from the box silhouette and from the projection of two parallel laser beams on one of the imaged faces of the box. In order to identify the box silhouette, we have developed a statistical model for homogeneous-background-color removal that works with a moving camera, and an efficient voting scheme for the Hough transform that allows the identification of almost collinear groups of pixels. We demonstrate the effectiveness of the proposed approach by automatically computing the dimensions of real boxes using a scanner prototype that implements the algorithms and methods described in the paper. We also present a discussion of the performed measurements, and an error propagation analysis that allows the method to estimate, from each single video frame, the uncertainty associated to all measurements made over that frame, in real-time.

Resumo em Inglês:

Test synthesis (or test generation) can be described as follows: from a formal specification of an implementation under test (IUT), and from a test purpose describing behaviors to be tested, the aim is to synthesize test cases to be executed in order to check whether the IUT conforms to its formal specification, while trying to control the IUT so that it satisfies the test purpose. In this paper, we study the synthesis of test cases for symbolic real-time systems. By symbolic, we mean that the specification of the IUT contains variables and parameters. And by real-time, we mean that the specification of the IUT contains timing constraints. Our method combines and generalizes two testing methods presented in previous work, namely: 1) a method for synthesizing test cases for (non-symbolic) real-time systems, and 2) a method for synthesizing test cases for (non-real-time) symbolic systems.

Resumo em Inglês:

Mutation Testing originated from a classical method for digital circuit testing and today is used at program and specification levels. It can be used either to generate or to assess the quality of test sets. In spite of being very effective in detecting faults, Mutation Testing is usually considered a high cost criterion due to: i) the large number of generated mutants; ii) the time-consuming activity of determining equivalent mutants; and iii) the mutant execution time. Many initiatives aiming at reducing the Mutation Testing application cost have been conducted, most of them addressing one of the drawbacks mentioned above. In this paper, we identify and summarize some of the most relevant researches and results related to Mutation Testing cost reduction, e.g., Constrained-Mutation, Constraint-Based Testing and Bayesian Learning. Moreover, we propose a Mutation Testing process, named Muta-Pro, that synergetically integrates the related approaches and mechanisms. This process is intended to be incremental and tailorable to a specific application domain such as C programs or finite state machine models. The main ideas in this paper are illustrated using a UNIX utility program. This process is being integrated in a Mutation Testing environment, based on the authors' previous experience on implementing the Proteum Family tools, aiming at promoting the technology transfer to industry and providing the basis for improving the Muta-Pro process itself.

Resumo em Inglês:

The number of open specifications of middleware systems and middleware services is increasing. Despite their complexity, they are traditionally described through APIs (the operation signatures) and informal prose (the behaviour). This fact often leads to ambiguities, whilst making difficult a better understanding of what is actually described. In this paper, we adopt software architecture principles for structuring middleware specifications together with LOTOS for formalising their behaviour. The adoption of software architecture principles makes explicit structural aspects of the middleware. Meanwhile, the formalisation enables us to check behavioural properties of the middleware. In order to illustrate our approach, we present a LOTOS specification of the well known object-oriented middleware CORBA.