肉骨粉显微近红外标准光谱库的快速构建方法

Rapid Construction of Near-infrared Microscopic Spectra Database for Identification of Meat and Bone Meal

利用傅里叶变换显微近红外成像系统,获取了3种不同种属肉骨粉骨颗粒样本的可见光图像和显微近红外图像。采用标记分水岭算法,基于Matlab软件和友好用户界面GUI设计实现图像颗粒的自动化提取与标记,以自动化批处理方式提高了光谱的提取效率,识别率为96.4%。基于颗粒标记,从三维显微成像数据阵中获取单条骨颗粒光谱,以全局马氏距离和邻近马氏距离为指标,提取其中具有代表性的光谱即可构建肉骨粉显微近红外标准光谱库。

A new strategy was demonstrated to establish typical spectra database.For the study,bone fragments of three different species MBM were analyzed on near-infrared microscopic imaging system,and both visible and near-infrared images were acquired at the same size.To extract and mark the position of every single bone fragment in visible image,a graphical user-friendly interface,based on marker-controlled watershed segmentation method,written in Matlab for extracting and marking bone fragments has been developed.The recognition ratio was 96.4%.By the position information in visible image,near-infrared microscopic imaging data was decompounded to spectrum of each bone fragment.Next,typical spectra were selected by the multivariate ＇distances＇—Global Hood（GH） Neighbor Hood（NH） statistics.