A new local binary pattern for smoke recognition

Gang Li; Hai Xia Hu; Xin Ai Xu

doi:10.1117/12.2653886

18 November 2022 A new local binary pattern for smoke recognition

Gang Li, Hai Xia Hu, Xin Ai Xu

Proceedings Volume 12473, Second International Conference on Optics and Communication Technology (ICOCT 2022); 124730T (2022) https://doi.org/10.1117/12.2653886
Event: Second International Conference on Optics and Communication Technology (ICOCT 2022), 2022, Hefei, China

Abstract

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.

Citation Download Citation

Gang Li, Hai Xia Hu, and Xin Ai Xu "A new local binary pattern for smoke recognition", Proc. SPIE 12473, Second International Conference on Optics and Communication Technology (ICOCT 2022), 124730T (18 November 2022); https://doi.org/10.1117/12.2653886

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