Forest fire detection and identification using image processing and SVM
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Accurate forest fires detection algorithms remain a challenging issue, because, some of the objects have thesame features with fire, which may result in high false alarms rate. This paper presents a new video-based, imageprocessing forest fires detection method, which consists of four stages. First, a background-subtractionalgorithm is applied to detect moving regions. Secondly, candidate fire regions are determined using CIEL∗a∗b∗ color space. Thirdly, special wavelet analysis is used to differentiate between actual fire and fire-likeobjects, because candidate regions may contain moving fire-like objects. Finally, support vector machine is usedto classify the region of interest to either real fire or non-fire. The final experimental results verify that theproposed method effectively identifies the forest fires.
Abstract
Accurate forest fires detection algorithms remain a challenging issue, because, some of the objects have thesame features with fire, which may result in high false alarms rate. This paper presents a new video-based, imageprocessing forest fires detection method, which consists of four stages. First, a background-subtractionalgorithm is applied to detect moving regions. Secondly, candidate fire regions are determined using CIEL∗a∗b∗ color space. Thirdly, special wavelet analysis is used to differentiate between actual fire and fire-likeobjects, because candidate regions may contain moving fire-like objects. Finally, support vector machine is usedto classify the region of interest to either real fire or non-fire. The final experimental results verify that theproposed method effectively identifies the forest fires.
참고문헌 (9)
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