期刊论文

Chen, Yuantao

英文

Cluster Computing

1386-7857

2019

22

3

S7665-S7675

10.1007/s10586-018-2368-8

This work is supported by the National Natural Science Foundation of China (No. 61702052), the Science and Technology Service Platform of Hunan Province (No. 2012TP1001), the Open Research Fund of Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation (No. 2015TP1005), the Changsha Science and Technology Planning (Nos. KQ1703018, KQ1706064), the Research Foundation of Education Bureau of Hunan Province (No. 12C0010, No. 17A007), the ZOOMLION Intelligent Technology Limited Company (No. 2017zkhx130), the Hunan Province Undergraduates Innovating Experimentation Project (No. (2016) 283-946), the Teaching and Reforming Project of Changsha University of Science and Technology (No. JG1755). We are grateful to anonymous referees for useful comments and suggestions.

本校为第一且通讯机构

For existed problems on fire detection fields, the traditional recognition methods on fire usually based on sensor’s signals are easily affected by the external environment elements. Meanwhile, most of the current methods based on feature extraction of fire image are less discriminative to different scene and fire type, and have lower recognition precision if the fire scene and type change. To overcome the drawback on fire recognition, the new fast recognition method for fire image has proposed by introducing color space information into Scale...