基于ELM理论的昆虫分类

Insect Classification Based on the Theory of the ELM

机器视觉技术应用在昆虫分类领域,取代传统人眼观察识别过程、提高了工作效率。自动识别技术包含昆虫特征提取和分类器设计两个主要步骤。根据整个识别过程,文中提出了一种基于混合特征的ELM理论昆虫识别方法。在特征提取阶段,提取混合特征包括颜色特征、形态特征、空域纹理特征和频谱纹理特征。在分类器设计阶段采用具有学习速度快且泛化性能好的极限学习机。实验结果表明,该方法使昆虫识别的正确率达到97%,且分类器训练时间短,优于传统的自动识别方法。

Applied in the field of insect taxonomy, machine vision technology displaces the human eye observa-tion identification process and improves working efficiency. The automatic identification technology has two mainsteps insects feature extraction and classifier design. Based on the entire identification process, this paper puts for-ward an insect identification method based on hybrid features of ELM theory. In the feature extraction stage, the hy-brid features will be extracted including the color, morphological characteristics, spatial texture, and spectral tex-ture; while in the classifier design stage, high learning speed and good generalization performance ELM extremelearning machine are taken. The experimental results show that this method offers an insect identification accuracy upto 97% with a short classifier training time, superior to the traditional automatic identification method.