A secret sharing scheme based on exponentiation in Galois fields

To provide more efficient and flexible alternatives for the applications of secret sharing schemes, this paper describes a threshold sharing scheme based on exponentiation of matrices in Galois fields. A significant characteristic of the proposed scheme is that each participant has to keep only one master secret share which can be used to reconstruct different group secrets according to the number of threshold values.

An integral security kernel

As the user base of the Internet has grown tremendously, the need for secure services has increased accordingly. Most secure protocols, in digital business and other fields, use a combination of symmetric and asymmetric cryptography, random generators and hash functions in order to achieve confidentiality, integrity, and authentication. Our proposal is an integral security kernel based on a powerful mathematical scheme from which all of these cryptographic facilities can be derived. The kernel requires very little resources and has the flexibility of being able to trade off speed, memory or security; therefore, it can be efficiently implemented in a wide spectrum of platforms and applications, either software, hardware or low cost devices. Additionally, the primitives are comparable in security and speed to well known standards.

A public key cryptosystem based on block upper triangular matrices

We propose a public key cryptosystem based on block upper triangular matrices. This system is a variant of the Discrete Logarithm Problem with elements in a finite group, capable of increasing the difficulty of the problem while maintaining the key size. We also propose a key exchange protocol that guarantees that both parties share a secret element of this group and a digital signature scheme that provides data authenticity and integrity.

A neural network algorithm to simplify 2D meshes

In this paper we propose a neural network model to simplify and 2D meshes. This model is based on the Growing Neural Gas model and is able to simplify any mesh with different topologies and sizes. A triangulation process is included with the objective to reconstruct the mesh. This model is applied to some problems related to urban networks.

Representation of 2D objects with a topology preserving network

Comunicación presentada en el 2nd International Workshop on Pattern Recognition in Information Systems, Alicante, April, 2002.

Event-based visual servoing

Traditional visual servoing systems have been widely studied in the last years. These systems control the position of the camera attached to the robot end-effector guiding it from any position to the desired one. These controllers can be improved by using the event-based control paradigm. The system proposed in this paper is based on the idea of activating the visual controller only when something significant has occurred in the system (e.g. when any visual feature can be loosen because it is going outside the frame). Different event triggers have been defined in the image space in order to activate or deactivate the visual controller. The tests implemented to validate the proposal have proved that this new scheme avoids visual features to go out of the image whereas the system complexity is reduced considerably. Events can be used in the future to change different parameters of the visual servoing systems.

Event-based visual servoing with features’ prediction

Event-based visual servoing is a recently presented approach that performs the positioning of a robot using visual information only when it is required. From the basis of the classical image-based visual servoing control law, the scheme proposed in this paper can reduce the processing time at each loop iteration in some specific conditions. The proposed control method enters in action when an event deactivates the classical image-based controller (i.e. when there is no image available to perform the tracking of the visual features). A virtual camera is then moved through a straight line path towards the desired position. The virtual path used to guide the robot improves the behavior of the previous event-based visual servoing proposal.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.