一种新的烟雾识别局部二值模式

Gang Li, Haixia Hu, XinAi Xu
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引用次数: 0

摘要

为了提高烟雾识别的检出率,降低误报率和错误率,提出了一种新的局部二值模式(zzag local binary pattern, ZLBP)。在ZLBP中,我们首先将局部区域的像素通过四个方向的四条之字形重新排列成四个线性区域,然后设计两种线性区域的编码方法。对于四个线性区域,我们可以得到四个特征向量,每个特征向量都是基于同一线性区域的两个编码来计算的。最后,我们将四个特征向量连接起来生成ZLBP特征。实验结果表明,该方法是有效的,适用于烟雾识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new local binary pattern for smoke recognition
In order to improve the detection rate of smoke recognition and reduce the false positive and error rates, a new local binary pattern (Zigzag Local Binary Pattern, ZLBP) is proposed. In ZLBP, we first rearrange the pixels in the local area into four linear areas by four zigzags with four directions, and then design two coding methods for the linear areas. For four linear areas, we can get four feature vectors, each of which is computed based on two codes of the same linear area. Finally, we concatenate the four feature vectors to generate ZLBP feature. Experimental results show that the new proposed pattern is effective and suitable for smoke identification.
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