Wu Wei, Chen Gui-Yun, Wu Ming-Qing, Yu Zhen-Wei, Chen Kun-Jie
Appl Opt. 2017 Mar 20;56(9):D72-D78. doi: 10.1364/AO.56.000D72.
A two-dimensional (2D) scatter plot method based on the 2D hyperspectral correlation spectrum is proposed to detect diluted blood, bile, and feces from the cecum and duodenum on chicken carcasses. First, from the collected hyperspectral data, a set of uncontaminated regions of interest (ROIs) and four sets of contaminated ROIs were selected, whose average spectra were treated as the original spectrum and influenced spectra, respectively. Then, the difference spectra were obtained and used to conduct correlation analysis, from which the 2D hyperspectral correlation spectrum was constructed using the analogy method of 2D IR correlation spectroscopy. Two maximum auto-peaks and a pair of cross peaks appeared at 656 and 474 nm. Therefore, 656 and 474 nm were selected as the characteristic bands because they were most sensitive to the spectral change induced by the contaminants. The 2D scatter plots of the contaminants, clean skin, and background in the 474- and 656-nm space were used to distinguish the contaminants from the clean skin and background. The threshold values of the 474- and 656-nm bands were determined by receiver operating characteristic (ROC) analysis. According to the ROC results, a pixel whose relative reflectance at 656 nm was greater than 0.5 and relative reflectance at 474 nm was lower than 0.3 was judged as a contaminated pixel. A region with more than 50 pixels identified was marked in the detection graph. This detection method achieved a recognition rate of up to 95.03% at the region level and 31.84% at the pixel level. The false-positive rate was only 0.82% at the pixel level. The results of this study confirm that the 2D scatter plot method based on the 2D hyperspectral correlation spectrum is an effective method for detecting diluted contaminants on chicken carcasses.
提出了一种基于二维高光谱相关光谱的二维散点图方法,用于检测鸡胴体盲肠和十二指肠处的稀释血液、胆汁和粪便。首先,从收集到的高光谱数据中,选择一组未受污染的感兴趣区域(ROIs)和四组受污染的ROIs,其平均光谱分别被视为原始光谱和受影响光谱。然后,获得差异光谱并进行相关分析,利用二维红外相关光谱的类比方法构建二维高光谱相关光谱。在656和474nm处出现了两个最大自峰和一对交叉峰。因此,选择656和474nm作为特征波段,因为它们对污染物引起的光谱变化最敏感。利用474nm和656nm空间中污染物、清洁皮肤和背景的二维散点图来区分污染物与清洁皮肤和背景。通过接收器操作特征(ROC)分析确定474nm和656nm波段的阈值。根据ROC结果,将656nm处相对反射率大于0.5且474nm处相对反射率小于0.3的像素判断为受污染像素。在检测图中标记识别出的像素数超过50的区域。该检测方法在区域水平上的识别率高达95.03%,在像素水平上为31.84%。在像素水平上的误报率仅为0.82%。本研究结果证实,基于二维高光谱相关光谱的二维散点图方法是检测鸡胴体上稀释污染物的有效方法。