Black Spot: a platform for automated and rapid estimation of leaf area from scanned images
Black Spot: a platform for automated and rapid estimation of leaf area from scanned images
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DOI：
10.1007/s11258-013-0273-z
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发表时间：
2013-12-01
期刊：
影响因子：
1.7
通讯作者：
Osuri, Anand M.
中科院分区：
文献类型：
--
作者：
Varma, Varun;Osuri, Anand M.
叶面积及其衍生物（如比叶面积）广泛应用于生态评估，特别是在植物-动物相互作用、植物群落组装、生态系统功能和全球变化等领域。估算叶面积是非常耗时的，即使使用专门的软件来处理扫描的叶片图像，因为手动输入总是需要规模检测和叶片表面数字化。我们介绍了黑点叶面积计算器（以下简称黑点），一种技术和独立的软件包，用于快速和自动化的叶面积评估，从图像的叶子与标准的平板扫描仪。Black Spot采用全面的色带比率规则集进行基于像素的分类，将叶片表面与图像背景隔离开来。重要的是，该软件从相关的图像元数据中提取信息来检测图像比例，从而消除了耗时的手动比例校准的需要。Black Spot的输出为用户提供了叶面积的估计值以及用于错误检查的分类图像。我们测试了这种方法和软件的组合，从现场收集的51种不同植物的100片叶子。使用黑点和通过使用图像编辑软件手动处理图像生成的叶面积估计值生成统计上相同的结果。相对于人工处理，从黑斑叶面积估计的平均误差率为-0.4%（SD = 0.76）。Black Spot的主要优势是能够以最小的用户努力和低成本快速批量处理多物种数据集，从而使其成为野外生态学家的宝贵工具。
Leaf area and its derivatives (e.g. specific leaf area) are widely used in ecological assessments, especially in the fields of plant-animal interactions, plant community assembly, ecosystem functioning and global change. Estimating leaf area is highly time-consuming, even when using specialized software to process scanned leaf images, because manual inputs are invariably required for scale detection and leaf surface digitisation. We introduce Black Spot Leaf Area Calculator (hereafter, Black Spot), a technique and stand-alone software package for rapid and automated leaf area assessment from images of leaves taken with standard flatbed scanners. Black Spot operates on comprehensive rule-sets for colour band ratios to carry out pixel-based classification which isolates leaf surfaces from the image background. Importantly, the software extracts information from associated image meta-data to detect image scale, thereby eliminating the need for time-consuming manual scale calibration. Black Spot's output provides the user with estimates of leaf area as well as classified images for error checking. We tested this method and software combination on a set of 100 leaves of 51 different plant species collected from the field. Leaf area estimates generated using Black Spot and by manual processing of the images using an image editing software generated statistically identical results. Mean error rate in leaf area estimates from Black Spot relative to manual processing was -0.4 % (SD = 0.76). The key advantage of Black Spot is the ability to rapidly batch process multi-species datasets with minimal user effort and at low cost, thus making it a valuable tool for field ecologists.