High-capacity quantum key distribution using Chebyshev-map values corresponding to Lucas numbers coding

We propose an approach that achieves high-capacity quantum key distribution using Chebyshev-map values corresponding to Lucas numbers coding. In particular, we encode a key with the Chebyshev-map values corresponding to Lucas numbers and then use k-Chebyshev maps to achieve consecutive and flexible key expansion and apply the pre-shared classical information between Alice and Bob and fountain codes for privacy amplification to solve the security of the exchange of classical information via the classical channel. Consequently, our high-capacity protocol does not have the limitations imposed by orbital angular momentum and down-conversion bandwidths, and it meets the requirements for longer distances and lower error rates simultaneously.     

Pose-invariant face recognition by matching on multi-resolution MRFs linked by supercoupling transform

Recognition of faces in arbitrary pose is addressed in this paper. For this task, an MRF-based classification approach is proposed which employs the energy of the established match between a pair of images as a criterion of goodness-of-match. By incorporating an image matching method as part of the recognition process, the system is made robust to moderate global spatial transformations. The approach draws on a method [1] which has the potential to cope with pose changes but a direct application of which suffers from several shortcomings. In order to overcome these problems, a number of enhancements are proposed. First, by adopting a multi-scale relaxation scheme based on super coupling transform, the inference using sequential tree re-weighted message passing approach [2] is accelerated. Next, by taking advantage of a statistical shape prior for the matching, the results are regularized and constrained, making the system robust to spurious structures and outliers. For classification, both textural and structural similarities of the facial images are taken into account. The method is evaluated on two databases and promising results are obtained.     

Incremental Linear Discriminant Analysis Using Sufficient Spanning Sets and Its Applications

This paper presents an incremental learning solution for Linear Discriminant Analysis (LDA) and its applications to object recognition problems. We apply the sufficient spanning set approximation in three steps i.e. update for the total scatter matrix, between-class scatter matrix and the projected data matrix, which leads an online solution which closely agrees with the batch solution in accuracy while significantly reducing the computational complexity. The algorithm yields an efficient solution to incremental LDA even when the number of classes as well as the set size is large. The incremental LDA method has been also shown useful for semi-supervised online learning. Label propagation is done by integrating the incremental LDA into an EM framework. The method has been demonstrated in the task of merging large datasets which were collected during MPEG standardization for face image retrieval, face authentication using the BANCA dataset, and object categorisation using the Caltech101 dataset.     

Coding of watershed and river hierarchy to support GIS-based hydrological analyses at different scales

A procedure is presented to automatically assign a modified Pfafstetter code to a stream network and its associated watersheds. The first step is to build a topological network according to the object-oriented Arc Hydro framework definition in ArcGIS. These network relations are then mapped into a code that fully represents the stream hierarchy of a basin in a single attribute. Its use does not depend on ArcGIS object orientation and facilitates simple hierarchical aggregation and querying using only the attribute tables of shapefile versions of the stream network and watershed datasets. The code was implemented for the whole of Austria to support the flexible presentation and user-defined aggregation of water balance results in the digital version of the Hydrological Atlas of Austria.     

Evaluation of six night vision enhancement systems: qualitative and quantitative support for intelligent image processing

OBJECTIVE: An evaluation study was conducted to answer the question of which system properties of night vision enhancement systems (NVESs) provide a benefit for drivers without increasing their workload. BACKGROUND: Different infrared sensor, image processing, and display technologies can be integrated into an NVES to support nighttime driving. Because each of these components has its specific strengths and weaknesses, careful testing is required to determine their best combination. METHOD: Six prototypical systems were assessed in two steps. First, a heuristic evaluation with experts from ergonomics, perception, and traffic psychology was conducted. It produced a broad overview of possible effects of system properties on driving. Based on these results, an experimental field study with 15 experienced drivers was performed. Criteria used to evaluate the development potential of the six prototypes were the usability dimensions of effectiveness, efficiency, and user satisfaction (International Organization for Standardization, 1998). RESULTS: Results showed that the intelligibility of information, the easiness with which obstacles could be located in the environment, and the position of the display presenting the output of the system were of crucial importance for the usability of the NVES and its acceptance. Conclusion: All relevant requirements are met best by NVESs that are positioned at an unobtrusive location and are equipped with functions for the automatic identification of objects and for event-based warnings. APPLICATION: These design recommendations and the presented approach to evaluate the systems can be directly incorporated into the development process of future NVESs.     

Constructive Membership Predicates as Index Types

In the constructive setting, membership predicates over recursive types are inhabited by terms indexing the elements that satisfy the criteria for membership. In this paper, we motivate and explore this idea in the concrete setting of lists and trees. We show that the inhabitants of membership predicates are precisely the inhabitants of a generic shape type. We show that membership of x (of type T) in structure S, (x_TS) can not, in general, index all parts of a structure S and we generalize to a form ρS where ρ is a predicate over S. Under this scheme, (λx.True)S is the set of all indexes into S, but we show that not all subsets of indexes are expressible by strictly local predicates. Accordingly, we extend our membership predicates to predicates that retain state “from above” as well as allow “looking below”. Predicates of this form are complete in the sense that they can express every subset of indexes in S. These ideas are motivated by experience programming in Nuprl's constructive type theory and examining the constructive content of mechanically checked formal proofs involving membership predicates.