Smoke detection for static cameras

A. Filonenko, Danilo Cáceres Hernández, K. Jo
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引用次数: 11

Abstract

This paper describes the smoke detection for static cameras. The background subtraction was used to determine moving objects. Color characteristics were utilized to distinguish smoke regions and other scene members. Separate pixels were united into blobs by morphology operations and connected components labeling methods. The image is then refined by boundary roughness and edge density to decrease amount of false detections. Results of the current frame are compared to the previous one in order to check the behavior of objects in time domain.
静态摄像机的烟雾检测
本文介绍了静态摄像机的烟雾检测。使用背景减法来确定运动物体。利用颜色特征来区分烟雾区域和其他场景成员。通过形态学运算和连通分量标记方法,将分离的像素点统一成blob。然后通过边界粗糙度和边缘密度对图像进行细化,以减少误检量。将当前帧的结果与前一帧的结果进行比较,以检查对象在时域中的行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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