Data visualization is producing images that communicate data in the form of visual objects like lines, points, bars, or colored areas. Often it is necessary to extract numerical data from these images for further analysis. There are a wide variety of data digitization tools, however, only limited formats of plot images can be digitized using them. There exists many data visualization formats spread across different domains of science. Some of these formats need tailored solutions. One such format is color mapped spectral power distribution images of light sources captured by proprietary spectrometers. In this work, a methodology is discussed to digitize spectral plots of light sources. Unlike typical digitization tools which extract data based on contrast difference, color, or morphological similarities, color mapped spectral plots contain blending colors across the x-axis, without containing any notable morphological features. In this work, image processing is applied to extract the contour representing a spectral plot. For color mapped spectral plots, the importance of appropriate binary input images for edge detection algorithms is highlighted. There are only a few edge-detection methods give the desired results except a few. Further, the importance of repeatedly adjusting threshold values in extracting desired contours is also discussed. The estimated and measured spectral parameters are in mutual agreement with each other thereby validating the adopted approach.

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关于数字化彩色映射光谱功率分布图像的技术说明

数据可视化正在生成图像，这些图像以线、点、条形或彩色区域等视觉对象的形式传达数据。通常有必要从这些图像中提取数值数据以进行进一步分析。有各种各样的数据数字化工具，但是，只有有限格式的绘图图像可以使用它们进行数字化。存在许多分布在不同科学领域的数据可视化格式。其中一些格式需要量身定制的解决方案。一种这样的格式是由专有光谱仪捕获的光源的彩色映射光谱功率分布图像。在这项工作中，讨论了一种方法来数字化光源的光谱图。与基于对比度差异、颜色或形态相似性提取数据的典型数字化工具不同，颜色映射的光谱图包含跨 x 轴的混合颜色，不包含任何显着的形态特征。在这项工作中，应用图像处理来提取表示光谱图的轮廓。对于彩色映射光谱图，强调了适当的二进制输入图像对边缘检测算法的重要性。除了少数之外，只有少数边缘检测方法可以提供所需的结果。此外，还讨论了在提取所需轮廓时重复调整阈值的重要性。估计和测量的光谱参数相互一致，从而验证了所采用的方法。对于彩色映射光谱图，强调了适当的二进制输入图像对边缘检测算法的重要性。除了少数之外，只有少数边缘检测方法可以提供所需的结果。此外，还讨论了在提取所需轮廓时重复调整阈值的重要性。估计和测量的光谱参数相互一致，从而验证了所采用的方法。对于彩色映射光谱图，强调了适当的二进制输入图像对边缘检测算法的重要性。除了少数之外，只有少数边缘检测方法可以提供所需的结果。此外，还讨论了在提取所需轮廓时重复调整阈值的重要性。估计和测量的光谱参数相互一致，从而验证了所采用的方法。