Image Processing Based Forest Fire Detection
A novel approach for forest fire detection using image processing technique and a rule based color model for fire pixel classification is used, which has both higher detection rate and lower false alarm rate.
Abstract
A novel approach for forest fire detection using image processing technique is proposed. A rule based color model for fire pixel classification is used. The proposed algorithm uses RGB and YCbCr color space. The advantage of using YCbCr color space is that it can separate the luminance from the chrominance more effectively than RGB color space. The performance of the proposed algorithm is tested on two sets of images, one of which contains fire; the other contains fire-like regions. Standard methods are used for calculating the performance of the algorithm. The proposed method has both higher detection rate and lower false alarm rate. Since, the algorithm is cheap in computation it can be used for real time forest fire detection. KEYWORDS: Forest fire detection, image processing, rule based color model, image segmentation. Language: en