The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 925–928, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-925-2017
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 925–928, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-925-2017

  13 Sep 2017

13 Sep 2017

RESEARCH ON FOREST FLAME RECOGNITION ALGORITHM BASED ON IMAGE FEATURE

Z. Wang, P. Liu, and T. Cui Z. Wang et al.
  • School of Urban and Environmental Sciences, Tianjin Normal University, Tianjin, China

Keywords: Forest Fire, Image Processing, Feature Analysis, Color Model, Cluster Analysis, Flame Recognition

Abstract. In recent years, fire recognition based on image features has become a hotspot in fire monitoring. However, due to the complexity of forest environment, the accuracy of forest fireworks recognition based on image features is low. Based on this, this paper proposes a feature extraction algorithm based on YCrCb color space and K-means clustering. Firstly, the paper prepares and analyzes the color characteristics of a large number of forest fire image samples. Using the K-means clustering algorithm, the forest flame model is obtained by comparing the two commonly used color spaces, and the suspected flame area is discriminated and extracted. The experimental results show that the extraction accuracy of flame area based on YCrCb color model is higher than that of HSI color model, which can be applied in different scene forest fire identification, and it is feasible in practice.