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An Efficient Algorithm Proposed For Smoke Detection in Video Using Hybrid Feature Selection Techniques

机译:提出一种使用混合特征选择技术的视频烟雾检测有效算法

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As an emerging development in the digital technology era, video processing is useful in a wide range of applications. In the current paper, an algorithm is proposed which is useful for smoke detection in video processing. The algorithm quickly detects fire by eliminating common interruptions like noise, overlapping due to the collision, etc. The proposed algorithm is composed of several techniques such as Haar feature, Bhattacharya distance method, SIFT descriptors, Gabor wavelets approach and SVM classifier to identify the smoke by video processing. Foreground object is identified using a moving object algorithm by predicting the movement of smoke in stable images. The implementation has been carried out in MATLAB.
机译:作为数字技术时代的新兴发展,视频处理在广泛的应用中很有用。在本文中,提出了一种算法,可用于视频处理中的烟雾检测。该算法通过消除噪声,碰撞引起的重叠等常见中断来快速检测火灾。所提出的算法由Haar特征,Bhattacharya距离方法,SIFT描述子,Gabor小波方法和SVM分类器等多种技术组成,以识别烟雾通过视频处理。通过预测稳定图像中烟雾的运动,使用运动物体算法来识别前景物体。该实现已在MATLAB中进行。

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