The paper presents a first prototype of a handheld museum guide delivering contextualized information based on the recognition of drawing details selected by the user through the guide camera. The resulting interaction modality has been analyzed and compared to previous approaches. Finally, alternative, more scalable, solutions are presented that preserve the most interesting features of the system described.

The classic nonlinear filter performs well in impulse noise suppression and edge preserving. However, the classic nonlinear filtering is not good at reducing the mixture of Gaussian noise and impulse noise. In this paper, we investigate the nonlinear filtering techniques to eliminate the mixture of impulse noise and Gaussian noise. Based on fuzzy theory, we present a weighted average filter by making use of the fuzzy membership functions to optimize the weights of the filter. Computational results, which have been obtained from experiments for noise attenuation, indicate that the new algorithm is promising.

This paper provides a simple introduction to the reconstructions and data-handling tools stored on the Edinburgh Mouse Atlas CD, together with some of the ways in which the viewers and software can be used to understand mouse development and analyse data. The key aspect of the Mouse Atlas is that the underlying models are a complete representation of the histology, which has not been constrained to a particular interpretation. This means, for example, that the current anatomy domains can be further subdivided as required to any resolution up to the resolution of the models (2-7 microm). In the CD of the early embryos described here, virtually all tissues that can be usefully distinguished either by the histology or morphologically have been delineated.

While many systems are currently available supporting the query-by-example paradigm for image retrieval, some key issues, such as the effective introduction of relevance feedback and the automatic selection of an optimal search strategy, need further investigation. This paper discusses query splitting as a way to improve the effectiveness of relevance feedback techniques based on feature weighting. The possibility of selecting among a set of image retrieval strategies the one which optimizes speed and quality on each given query is also presented and discussed.

A currently important research field in information sciences is the management of nontraditional distributed multimedia databases. Two related key issues are to achieve an efficient content-based query by example retrieval and a fast response time. This paper presents the architecture of a distributed image retrieval system which provides novel solutions to these key issues. In particular, a method to quantify the effectiveness of low level visual descriptors in database query tasks is presented. The results are also used to improve the system response time, which is an important issue when querying very large databases. A new mechanism to adapt system query strategies to user behavior is also introduced in order to improve the effectiveness of relevance feedback and overall system response time. Finally, the issue of browsing multiple distributed databases is considered and a solution is proposed using multidimensional scaling techniques.

This paper presents a person identification system based on acoustic and visual features. The system is organized as a set of non-homogeneous classifiers whose outputs are integrated after a normalization step. In particular, two classifiers based on acoustic features and three based on visual ones provide data for an integration module whose performance is evaluated. A novel technique for the integration of multiple classifiers at an hybrid rank/measurement level is introduced using HyperBF networks. Two different methods for the rejection of an unknown person are introduced. The performance of the integrated system is shown to be superior to that of the acoustic and visual subsystems. The resulting identification system can be used to log personal access and, with minor modifications, as an identity verification system.>

Two new algorithms for computer recognition of human faces, one based on the computation of a set of geometrical features, such as nose width and length, mouth position, and chin shape, and the second based on almost-gray-level template matching, are presented. The results obtained for the testing sets show about 90% correct recognition using geometrical features and perfect recognition using template matching.>