摘要
为解决成熟草莓在采摘运输过程中存在的早期损伤难以快速检测的问题,保障草莓的商业价值和食品安全,本研究提出一种基于高光谱成像技术的新方法,结合波段比和改进的分水岭分割算法,实现对草莓早期损伤的无损检测。在Vis-NIR(480.19~1015.63 nm)、Vis(480.19~780.0 nm)和NIR(780.0~1015.63 nm)3个光谱范围内进行主成分聚类分析,并通过主成分载荷图选定特征波长。此外生成对应的主成分图像和波段比图像,并采用改进的分水岭分割算法进行草莓损伤区域的分割。结果表明:1)在Vis-NIR和NIR光谱范围内,沿PC1的方向可以有效区分不同损伤部位的草莓。2)在波段比图像效果比较中,Q758.64/1015.63波段比图像在增强损伤对比度方面效果表现最佳,因此被选为最适合后续分析的波段比。3)改进的分水岭分割算法相较于传统的分水岭分割算法和改进的大津法,对损伤区域的分割效果更好,总体检测准确率达到95.5%,表明该方法在检测草莓早期损伤方面具有可靠性和有效性。综上,通过高光谱成像技术与改进的分水岭分割算法结合对草莓的早期损伤进行快速无损检测具有一定可行性,为草莓品质保障和食品安全提供了理论和技术支持。
In order to solve the problem of early damage of ripe strawberries during picking and transport,which is difficult to detect quickly,and to safeguard the commercial value and food safety of strawberries,this study proposes a new method based on hyperspectral imaging technology,which combines the band ratio and the improved watershed segmentation algorithm,to realize non-destructive detection of early damage of strawberries.Principal component cluster analysis was conducted across three spectral ranges:Vis-NIR(480.19~1015.63 nm),Vis(480.19~780.0 nm),and NIR(780.0~1015.63 nm).Characteristic wavelengths were identified using principal component loading maps.Subsequently,corresponding principal component and band ratio images were generated.The segmentation of strawberry damage regions was performed using an improved watershed segmentation algorithm.The results indicate that:1)Strawberries with different damage areas can be effectively differentiated in the Vis-NIR and NIR spectral ranges,along the PC1 direction.2)Among the band ratio images,the Q758.64/1015.63 band ratio image exhibits the best performance in enhancing damage contrast,making it the most suitable for subsequent analysis.3)The improved watershed segmentation algorithm outperforms the traditional watershed and improved Otsu methods,achieving an overall detection accuracy of 95.5%,demonstrating its reliability and effectiveness in detecting early strawberry damage.In conclusion,the integration of hyperspectral imaging technology with the improved watershed segmentation algorithm is a viable approach for the rapid,nondestructive detection of early strawberry damage,offering theoretical and technical support for ensuring strawberry quality and food safety.
作者
刘燕德
刘良峰
李雄
姚迟
欧阳爱国
LIU Yande;LIU Liangfeng;LI Xiong;YAO Chi;OUYANG Aiguo(School of Intelligent Electromechnical Equipment Innovation Research institute,East China Jiaotong University,Nanchang 330013,China)
出处
《中国农业大学学报》
CAS
CSCD
北大核心
2024年第11期50-62,共13页
Journal of China Agricultural University
基金
国家自然科学基金项目(31760344)。
关键词
高光谱成像
损伤检测
波段比
改进的分水岭分割算法
草莓
hyperspectral imaging
damage detection
band ratio
improved watershed segmentation algorithm
strawberry
