标题：Flame detection algorithm based on a saliency detection technique with prior information in the YCbCr color space
作者：Liu, Zhao-Guang; Yang, Yang; Liu, Yun-Xia
作者机构：[Liu, Zhao-Guang] Shandong Univ Finance & Econ, Sch Comp Sci & Technol, Shandong Prov Key Lab Digital Media Technol, Jinan, Peoples R China.; [Yang, 更多
会议名称：IEEE 7th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
会议日期：DEC 20-21, 2014
来源：2014 IEEE 7TH JOINT INTERNATIONAL INFORMATION TECHNOLOGY AND ARTIFICIAL INTELLIGENCE CONFERENCE (ITAIC)
关键词：flame detection; saliency detection; probability density function; YCbCr; color space
摘要：Computer vision-based fire detection involves flame detection and smoke detection. This paper proposes a new flame detection algorithm, which is based on a saliency detection technique with prior information in color space. In still images and video sequences, an area containing a flame always attracts the attention because it is an exceptional event. Thus, to utilize the color information of flame pixels, the probability density function of the flame pixel color can be obtained using Parzen window nonparametric estimation. This prior probability density function is then fused with the saliency detection phase as top-down information so the flame candidate area can be extracted. According to the experimental results, our proposed method can reduce the number of false alarms greatly compared with an alternative algorithm, while it also ensures the accurate classification of positive samples. The classification performance of our proposed method was better than that of alternative algorithms.