基于静态背景差分的阈值算法在果实识别中的应用

图像识别是当前人工智能发展的1个热点。针对农业果园采集图像光照不均匀,背景复杂多样等特点,提出了一种基于静态背景差分的最大类间方差改进算法用于果园复杂背景图像的分割。通过调节参数γ达到不同对比度下果实与背景环境的最佳分割。然后利用距离变换和分水岭算法进行粘连果实的分离,实现果实图像的识别,并且通过实验分析和计算确定了最佳参数γ范围在0.2~0.3之间。实验验证表明,图像识别效果良好,能够为果园品质在线检测提供很好的技术基础。

The Application of Static Background Subtraction in OTSU for Fruit Recognition

Image recognition is a hotspot in the development of artificial intelligence . Due to theuneven illumination and complex background of imagescollected from orchard agriculture ,this paper proposed a new improved OTSU which is based on static background subtraction algorithm .By adjusting the parameters γto achieve optimal segmented fruit under different contrast with the background environment ,the researchers use the distance transform watershed algorithm to separate adhesions fruit ,and determine the optimum parameter γrange between 0.2 to 0.3 viaexperimental analysis and calculations .Results show that the image recognition works well ,whichcan provide a good foundation for the technical quality of the orchard online testing .