Reduction of false alarm rate in automatic forest fire infrared surveillance systems

One of the main problems related to infrared remote sensing of forest fires by automatic systems concerns the rejection of false alarms. The study of the infrared spectral radiance emitted by a biomass fire has been used to define spectral algorithms that permit to separate fires from other sources considered as false alarms. The different behaviour of the medium (3-5 μm) and thermal (8-12 μm) infrared spectral regions has been the basis for the definition of a new “figure” of merit, the so-called Fire Index (FI). An experimental burn has been used to test the ability of FI to identify clearly fires. A second algorithm based on an intraband analysis, the Mid-IR Fire Index (MFI), has been proposed to give complementary information to FI. Evolution of FI and MFI values with distance for different IR sources has been calculated. Finally, an experimental validation of both algorithms has been performed by using two infrared cameras working in the medium and thermal infrared spectral windows.     

The constant false alarm rate property in transformed noncoherent detection processes

Recently a transformation approach for noncoherent radar detector design has been introduced, where the classical constant false alarm rate detectors for Exponentially distributed clutter are modified to operate in any clutter intensity model of interest. Recent applications of this approach have introduced new decision rules for target detection in Pareto and Weibull distributed clutter. These transformed detectors tended to lose the constant false alarm rate property with respect to one of the clutter parameters. A closer examination of this transformation process yields conditions under which the constant false alarm rate property can be retained. Based upon this, a new model for X-band maritime radar returns is investigated, and corresponding detectors are developed. The relative merits of this new development are investigated with synthetic and real X-band data.     

Constant false alarm rate detection of saccadic eye movements in electro-oculography

The analysis of eye movements has proven to be valuable in both clinical work and research as well as in other fields besides medicine. The detection of saccadic eye movements and the extraction of related saccade parameters, such as maximum angular velocity, amplitude, and duration, are usually performed during the analysis of electro-oculographic (EOG) signals. This article considers a saccade detection method that is based on the constant false alarm rate technique, in which the detection sensitivity is continuously adjusted on the basis of the observed signal in order to keep the number of false alarms constant. The method is computationally efficient, it can operate autonomously without user intervention, and it is capable of detecting saccades in a sequential fashion. Therefore, the method finds potential use in applications that require automated analysis of electro-oculographic signals. Because of the constant false alarm rate property, the method can also perform in situations where ideal measurement conditions cannot be guaranteed and noise presents a considerable problem.     

基于Laplacian Eigenmap的图像变化检测虚警优化技术

对点目标的图像变化检测,现有的变化检测技术结果往往存在着虚警过大的问题。通过深入分析多个传统的变化检测方法的特点,利用各方法的互补性,提出了利用Laplacian Eigenmap对多个方法检测结果进行降维分类的优化技术。首先把各个方法对某个像素的检测结果用向量的形式进行表示,然后利用Laplacian Eigenmap对整个图像的数据流形在低维空间展开,最后利用模糊分类进行分类。该技术有两个优势：（1）在保证现有较高检测率的同时,大大降低了结果的虚警率;（2）它极大地降低了在传统方法中由于人为阈值取舍带来的偏差风险。但该技术的不足之处是增加了计算量。     

长度归一化扫描的合成孔径雷达图像船舶尾迹恒虚警率检测

提出一种基于长度归一化扫描的合成孔径雷达(SAR)图像船舶尾迹检测算法.存在距离向运动分量的船舶在SAR图像上会发生方位向偏移,那么尾迹的起点必在方位向上这一偏移量范围内.根据这一物理事实,将尾迹检测的搜索范围限定在可能为尾迹的线段上,从而提高了检测效率.算法通过利用线性积分和长度归一化这两个方法将矩形滑动窗口下的线性特征检测转化为了点特征检测,并通过经典的虚警率(CFAR)检测理论实现检测结果的输出.利用COSMO-SkyMed数据对该算法进行了实验验证,实验结果表明,该算法在尾迹检测上具有检测能力强、速度快的优点,船舶速度反演具有较高精度.     

The impact of dust in filter materials of respiratory protective devices on the microorganisms viability

Plant biomass processed in a heat and power plant is a source of airborne dust present in the working environment. The aim of this study was to assess the influence of various levels of organic dust content in the filter material on the viability of microorganisms in model conditions, taking into consideration the workplace environment and the physico-chemical as well as the microbiological characteristics of the dust particles. The possibility of a biofilm developing on the reusable filtering facepiece respirators (FFR) in standard use by heat and power plant workers for respiratory tract protection was also investigated.Standard reusable filtering half masks FFP3R and high-performance melt-blown fabrics were used in the study. The biomass dust characteristics were determined using an elementary analyser and a condensation particle counter with an electrostatic classifier. For quantitative analysis of microbiological pollution we used the plate count method with the microorganisms identified either using the API biochemical tests (for bacteria and yeasts) and the taxonomic key (for moulds). Biofilm development on the filtering half masks was assessed using SEM scanning microscopy. The viability of microorganisms (namely Escherichia coli ATCC 10536, Staphylococcus aureus ATCC 6538, Candida albicans ATCC 10231, Aspergillus niger ATCC 16404; Bacillus subtilis NCAIM 01644) on the filter materials with different dust content was measured using the quantitative method AATCC 100-2004 (2008).In the plant biomass processed at the heat and power plant, a high concentration of bacteria (2.30 × 10⁷ CFU g⁻¹) and a lower concentration of fungi (4.46 × 10⁵ CFU g⁻¹) were detected. It was determined to be a good environment for the growth of microorganisms (the carbon to nitrogen ratio was 48:1). The presence of dust and the development of microbiological biofilms on reusable FFR, which is used by the heat and power plant workers for processing the plant biomass in increased humidity conditions, were also confirmed.It was found that the viability of microorganisms on a filter material depends on the kind of microorganism and the dust content on the material. Model research showed that biomass dust in filter materials stimulates the growth of E. coli. Moreover, dust concentration above 21% inhibited the growth of S. aureus and C. albicans but had no significant influence on the growth of B. subtilis and A. niger.     

The impact of false warnings on partial and full lane departure warnings effectiveness and acceptance in car driving

In the past, lane departure warnings (LDWs) were demonstrated to improve driving behaviours during lane departures but little is known about the effects of unreliable warnings. This experiment focused on the influence of false warnings alone or in combination with missed warnings and warning onset on assistance effectiveness and acceptance. Two assistance unreliability levels (33 and 17%) and two warning onsets (partial and full lane departure) were manipulated in order to investigate interaction. Results showed that assistance, regardless unreliability levels and warning onsets, improved driving behaviours during lane departure episodes and outside of these episodes by favouring better lane-keeping performances. Full lane departure and highly unreliable warnings, however, reduced assistance efficiency. Drivers’ assistance acceptance was better for the most reliable warnings and for the subsequent warnings. The data indicate that imperfect LDWs (false warnings or false and missed warnings) further improve driving behaviours compared to no assistance.

Practitioner Summary: This study revealed that imperfect lane departure warnings are able to significantly improve driving performances and that warning onset is a key element for assistance effectiveness and acceptance. The conclusion may be of particular interest for lane departure warning designers.