基于高光谱成像技术的灵武长枣缺陷识别OA北大核心CSCDCSTPCD
Non-destructive detection of defects inZizphus jujubeMill cv.Lingwu changzao based on near-infrared hyperspectral imaging
为研究快速识别灵武长枣表面裂痕、虫眼、碰伤等常见缺陷的有效方法,利用特征波长主成分分析法结合波段比算法进行长枣裂痕、虫眼、碰伤识别.首先,采用近红外(Near Infrared Reflection,NIR)波段范围的高光谱成像系统获取300个长枣反射图像,提取并分析各类型长枣光谱曲线,选择918~1 678 nm波段范围进行主成分分析,通过权重系数提取特征波长;然后,对特征波长下图像进行主成分分析,选择最优的主成分图像进行识别;最后,对未识别的…查看全部>>
Zizphus jujube Mill cv.Lingwu changzao, as one of characteristic agricultural products in Ningxia, is favored by the broad consumer for its high nutritional value. However, the external quality of long jujube will affect directly its sale and storage. In the traditional detection method, it has several disadvantages such as time-consuming, laborious and low efficiency, etc. Hyperspectral imaging technique has become an important trend to employ nondestructiv…查看全部>>
吴龙国;王松磊;康宁波;何建国;贺晓光
宁夏大学土木水利工程学院,银川 750021宁夏大学土木水利工程学院,银川 750021宁夏大学农学院,银川 750021宁夏大学土木水利工程学院,银川 750021宁夏大学土木水利工程学院,银川 750021
信息技术与安全科学
主成分分析缺陷高光谱成像无损检测长枣缺陷
principal component analysisdefectshyperspectral imagingnon-destructive detectionlong jujubes
《农业工程学报》 2015 (20)
灵武长枣采后光谱特征变化的生物光学机理研究
281-286,6
国家自然科学基金资助项目(31060233,31560481)2011年度宁夏回族自治区科技攻关计划项目 (2011HZF05J01)国家科技支撑计划(2012BAF07B06)
评论