A ground system for early forest fire detection based on infrared signal processing

This article presents a ground remote automatic system for forest surveillance based on infrared signal processing applied to early fire detection. Advanced techniques, which are based on infrared signal processing, are used in order to process the captured images. With the aim of determining the presence or absence of fire, the system performs the fusion of different detectors that exploit different expected characteristics of a real fire, such as persistence and increase. Theoretical simulations and practical results are presented to corroborate the control of the probability of false alarm. Results in a real environment are also presented to authenticate the accuracy of the operation of the proposed system. In particular, some experiments have been done to evaluate the delay of the system (tens of seconds on average) in detecting a controlled ground fire in a range of 1-10 km. Moreover, temporary evolution of false alarms and true detections are presented to evaluate the long-term performance of the system in a real environment. We have reached a detection probability of 100% at a false alarm rate of around 1 x 10(-9).This work has been supported by Generalitat Valenciana, under grant GVEMP06/001, and by MEC under the FPU programme.Bosch Roig, I.; Gómez, S.; Vergara Domínguez, L. (2011). A ground system for early forest fire detection based on infrared signal processing. International Journal of Remote Sensing. 32(17):4857-4870. https://doi.org/10.1080/01431161.2010.490245S485748703217Arrue, B. C., Ollero, A., & Matinez de Dios, J. R. (2000). An intelligent system for false alarm reduction in infrared forest-fire detection. IEEE Intelligent Systems, 15(3), 64-73. doi:10.1109/5254.846287Bernabeu, P., Vergara, L., Bosh, I., & Igual, J. (2004). A prediction/detection scheme for automatic forest fire surveillance. Digital Signal Processing, 14(5), 481-507. doi:10.1016/j.dsp.2004.06.003Briz, S. (2003). Reduction of false alarm rate in automatic forest fire infrared surveillance systems. Remote Sensing of Environment, 86(1), 19-29. doi:10.1016/s0034-4257(03)00064-6Pastor, E. (2003). Mathematical models and calculation systems for the study of wildland fire behaviour. Progress in Energy and Combustion Science, 29(2), 139-153. doi:10.1016/s0360-1285(03)00017-0Vergara, L., & Bernabeu, P. (2000). Automatic signal detection applied to fire control by infrared digital signal processing. Signal Processing, 80(4), 659-669. doi:10.1016/s0165-1684(99)00159-0Vergara, L., & Bernabeu, P. (2001). Simple approach to nonlinear prediction. Electronics Letters, 37(14), 926. doi:10.1049/el:20010616Vicente, J., & Guillemant, P. (2002). An image processing technique for automatically detecting forest fire. International Journal of Thermal Sciences, 41(12), 1113-1120. doi:10.1016/s1290-0729(02)01397-

Shadow detection using 2D cepstrum

Shadows constitute a problem in many moving object detection and tracking algorithms in video. Usually, moving shadow regions lead to larger regions for detected objects. Shadow pixels have almost the same chromaticity as the original background pixels but they only have lower brightness values. Shadow regions usually retain the underlying texture, surface pattern, and color value. Therefore, a shadow pixel can be represented as a.x where x is the actual background color vector in 3-D RGB color space and a is a positive real number less than 1. In this paper, a shadow detection method based on two-dimensional (2-D) cepstrum is proposed. © 2009 SPIE

EARLY FOREST FIRE DETECTION USING TEXTURE, BLOB THRESHOLD, AND MOTION ANALYSIS OF PRINCIPAL COMPONENTS

Forest fires constantly threaten ecological systems, infrastructure and human lives. The purpose behind this study is minimizing the devastating damage caused by forest fires. Since it is impossible to completely avoid their occurrences, it is essential to accomplish a fast and appropriate intervention to minimize their destructive consequences. The most traditional method for detecting forest fires is human based surveillance through lookout towers. However, this study presents a more modern technique. It utilizes land-based real-time multispectral video processing to identify and determine the possibility of fire occurring within the camera’s field of view. The temporal, spectral, and spatial signatures of the fire are exploited. The methods discussed include: (1) Range filtering followed by entropy filtering of the infrared (IR) video data, and (2) Principal Component Analysis of visible spectrum video data followed by motion analysis and adaptive intensity threshold. The two schemes presented are tailored to detect the fire core, and the smoke plume, respectively. Cooled Midwave Infrared (IR) camera is used to capture the heat distribution within the field of view. The fire core is then isolated using texture analysis techniques: first, range filtering applied on two consecutive IR frames, and then followed by entropy filtering of their absolute difference. Since smoke represents the earliest sign of fire, this study also explores multiple techniques for detecting smoke plumes in a given scene. The spatial and temporal variance of smoke plume is captured using temporal Principal Component Analysis, PCA. The results show that a smoke plume is readily segmented via PCA applied on the visible Blue band over 2 seconds sampled every 0.2 seconds. The smoke plume exists in the 2nd principal component, and is finally identified, segmented, and isolated, using either motion analysis or adaptive intensity threshold. Experimental results, obtained in this study, show that the proposed system can detect smoke effectively at a distance of approximately 832 meters with a low false-alarm rate and short reaction time. Applied, such system would achieve early forest fire detection minimizing fire damage. Keywords: Image Processing, Principal Component Analysis, PCA, Principal Component, PC, Texture Analysis, Motion Analysis, Multispectral, Visible, Cooled Midwave Infrared, Smoke Signature, Gaussian Mixture Model