Infrared image processing and its application to forest fire surveillance
This paper describes an scheme for automatic forest surveillance. A complete system for forest fire detection is firstly presented although we focus on infrared image processing. The proposed scheme based on infrared image processing performs early detection of any fire threat. With the aim of determining the presence or absence of fire, the proposed algorithms performs the fusion of different detectors which exploit different expected characteristics of a real fire, like persistence and increase. Theoretical results and practical simulations are presented to corroborate the control of the system related with probability of false alarm (PFA). Probability of detection (PD) dependence on sign…
Background noise suppression for acoustic localization by means of an adaptive energy detection approach
A microphone array can be employed to localize dominant acoustic sources in a given noisy environment. This capability is successfully used in good signal to noise ratio (SNR) conditions but its accuracy decreases considerably in the presence of other background noise sources. In order to counteract this effect, a novel approach that combines the information provided by a Gaussian energy detector (GED) with the approved localization method SRP-PHAT is presented in this paper. To evaluate the presented technique, several acoustic sources (speech and impulsive sounds) were considered in a variety of different scenarios to demonstrate the robustness and the accuracy of the system proposed.
Intelligent system for material quality control using impact-echo testing
This paper introduces an intelligent system to discern the quality of materials inspected by the impact-echo technique. The system includes a hardware setup to inspect parallelepiped-shape materials and a procedure to classify the material depending on its quality condition. Four levels of classification with different grades of knowledge about the material defects are approached: material condition, kind of defect, defect orientation, and defect dimension. The number of classes (material qualities) in the lowest classification level is 12. The procedure is applied on signals coming from 3D finite element simulations and lab experiments with aluminium specimens. The classification procedure…