采用高光谱成像技术对香梨的表面损伤缺陷进行准确高效的无损检测。选用80个库尔勒香梨为研究对象,采集400~1000 nm波段内完好样本和损伤样本的高光谱图像;利用统计分析的方法,选择863 nm处的高光谱图像建立掩模图像;运用主成分分析方法降低香梨高光谱数据的维度,选择损伤区域与背景区域光谱差异最为明显的第二主成分图像,将其和第四主成分图像进行比值处理,进一步增强损伤区域与背景区域的差异;最后经自适应阈值分割、形态学运算,提取香梨表面损伤区域。结果表明,该方法能够有效识别出香梨的表面损伤,准确度、精度和召回率分别为93.75%、87.50%和100%。

In this study, the hyperspectral imaging technology is employed for accurately and efficiently detecting the surface damage of Korla fragrant pears. Eighty fragrant pears were considered in this study. The hyperspectral images of the intact and damaged samples in the wavelength range of 400-1000 nm were obtained. The hyperspectral image obtained at 863 nm was selected to achieve image mask using the statistical analysis method. The dimension of hyperspectral data was reduced via principle component analysis. Subsequently, the second principle component image exhibiting the most considerable difference between the damaged and background areas was selected to compare with the fourth principle component image via the ratio method of image processing for enhancing the difference between the damaged area and the background area. Finally, the threshold segmentation and morphological operations were used to obtain the damaged areas on the surface of fragrant pears. Results denote that the proposed method can effectively identify the surface damage of fragrant pears. Furthermore, the accuracy, precision, and recall rate of the proposed method are 93.75%, 87.50%, and 100%, respectively.