Ignacio Melgar

Ant based edge linking algorithm

Conventional image edge detectors always result in missing parts of the edges. Broken edge linking is an image improvement technique that is complementary to edge detection, where the broken edges are connected to form closed contours in order to separate the regions in the image. In this paper, Ant System (AS) algorithm is modified for edge linking problem. As input, a binary image obtained after applying the Sobel edge operator is used. The proposed method defines a novel fitness function dependent on two variables: the grayscale visibility of the pixels and the length of the connecting edge, in order to obtain effective solution evaluation. Another novelty is of applying the grayscale visibility matrix as the initial pheromone trails matrix so that the pixels belonging to true edges have a higher probability of being chosen by ants on their initial routes, which reduces computational load. The results of the experiments are presented to confirm the effectiveness of the proposed method.

Swarm architectures for Ground-based Air Defense Systems of Systems

New generations of Ground based Air Defense Systems of Systems used in modernized Armed Forces maintain the architectures used in their previous versions, constrained by hierarchical radio communications and centralized Command and Control restrictions. Current state-of-the-art technology in these areas allows a refocusing of these architectures towards a swarm approach. Advantages in terms of effectiveness, scalability and survivability are identified, and a preliminary set of swarm algorithms are proposed and analyzed. Upgrades of these preliminary algorithms are proposed as future research areas.

Wavelet Time Shift Properties Integration with Support Vector Machines

This paper presents a short evaluation about the integration of information derived from wavelet non-linear-time-invariant (non-LTI) projection properties using Support Vector Machines (SVM). These properties may give additional information for a classifier trying to detect known patterns hidden by noise. In the experiments we present a simple electromagnetic pulsed signal recognition scheme, where some improvement is achieved with respect to previous work. SVMs are used as a tool for information integration, exploiting some unique properties not easily found in neural networks.

Optimization of System-of-Systems architectures for maritime border control using genetic algorithms

Engineering solutions to surveillance operations in wide areas are based on the integration of manned aircrafts and Unmanned Aerial Vehicles in complex System-of-Systems (SoS) architectures. The selection of one specific architecture depends on a very large set of parameters and constraints related to the surveillance scenario, target statistics and the availability of limited resources such as electro-magnetic spectrum, crew, airfields or simply budgetary restrictions. This paper covers the use of Genetic Algorithms (GA) to obtain the best SoS architecture for a given surveillance scenario and a given set of limited resources.

Combining edge detection algorithms in intensity SAR images

Edge-detection algorithms are applied to SAR images in order to generate different edge strength maps. The results obtained can be combined to improve the final output in order to get a more defined edge strength map. In this paper different combinations of methods are implemented and evaluated using a criterion based on the quality of the detected edges over the original image. The aspects considered are the false alarm rate, edge thickness and discontinuities inside the detected edges. The results obtained with the edge enhancement techniques are compared and conclusions about the best combination strategies are extracted.

Cooperation and competition based on free market in swarm system architectures for air defense

Algorithms to perform distributed Command and Control functions in Ground based Air Defense Systems of Systems are presented and analyzed. In previous research we presented the benefits of using swarm architectures for this type of application in terms of no single point of failure, lower detectability and higher scalability. Here we propose some Free Market distributed algorithms based on the principles of negotiation and competition among the swarm of agents performing air defense missions. In our research, parameter optimization as well as experimental results in tactical scenarios are obtained through simulation.

Discrete wavelet cycle integration for pulse detection

Current approaches in electromagnetic pulse detection (radar, communications, etc.) use domain transformations so as to concentrate in frequency related information that can be distinguishable from noise. Wavelet transforms are usually described in two main sets: continuous wavelet transforms and discrete wavelet transforms. Although they share mathematical motivation, both transformations have different algorithms and properties. The property we focus on is the time invariance (also called translation invariance). Continuous wavelets are time invariant, but they are also very expensive to calculate. Real time systems find it hard to process all that information with enough accuracy. On the other hand, uniformly sampling the translation parameter as input to the discrete wavelet process destroys this time invariance. In this paper we introduce experimental results that show an alternative way to generate a time invariant representation of a signal using discrete wavelet transforms. This algorithm upgrades the cost-efficiency of pulse detection capability with respect to the basic approach.