Multispectral imaging has been a valuable technique for discovering hidden texts in manuscripts, learning the provenance of antique books, and generally studying cultural heritage objects. Standard software used in displaying and analyzing such multispectral images are often complex and requires installation and maintenance of custom packages and libraries. We present an easy-to-use web-based multispectral imaging visualization tool that enables simultaneous interaction with the information captured in different spectral bands.
It is difficult to describe facial skin color through a solidcolor as it varies from region to region. In this article, the authors utilized image analysis to identify the facial color representative region. A total of 1052 female images from Humanae project were selected as a solid color was generated for each image as their representative skin colors by the photographer. Using the open CV-based libraries, such as EOS of Surrey Face Models and DeepFace, 3448 facial landmarks together with gender and race information were detected. For an illustrative and intuitive analysis, they then re-defined 27 visually important sub-regions to cluster the landmarks. The 27 sub-region colors for each image were finally derived and recorded in L*, a*, and b*. By estimating the color difference among representative color and 27 sub-regions, we discovered that sub-regions of below lips (low Labial) and central cheeks (upper Buccal) were the most representative regions across four major ethnicity groups. In future study, the methodology is expected to be applied for more image sources. c 2020 Society for Imaging Science and Technology.