Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, Florida 33431, USA.
J Acoust Soc Am. 2013 Jul;134(1):EL105-11. doi: 10.1121/1.4811162.
An image processing technique called Local Binary Patterns (LBP) has been explored for its ability to generate feature vectors for dolphin vocalization classification. The LBP operator eliminates the need for contour tracing, denoising, and other prior processing. In an experimental study of classifying dolphin whistle types, the performance of the LBP operation was compared with that of the popular contour-based Time-Frequency Parameters (TFP) approach. The preliminary experimental results illustrate that the LBP method produces more consistent classifier accuracy of dolphin whistle calls even when the contour shapes are complex and populated with impulsive clicks and anthropogenic harmonics.
一种称为局部二值模式（LBP）的图像处理技术因其能够为海豚发声分类生成特征向量而被探索。LBP 算子消除了对轮廓跟踪、去噪和其他预处理的需求。在一项对海豚哨声类型进行分类的实验研究中，将 LBP 操作的性能与流行的基于轮廓的时频参数（TFP）方法进行了比较。初步实验结果表明，即使轮廓形状复杂且充满脉冲点击和人为谐波，LBP 方法也能产生更一致的海豚哨声分类器准确性。
