Authors: Andrew M. Leisner (George Mason University), Jeremey A. Grajeda (New Mexico State University), C. Nick Arge (NASA/GSFC), Michael Kirk (ASTRA), Laura Boucheron (New Mexico State University), Jie Zhang (George Mason University)

Identifying coronal holes in solar disk images is very challenging, yet critical, as they serve as a key constraint for coronal models. In this poster, we discuss a process to create synchronic coronal hole maps, with coronal holes identified by both automatic and manual means in a set of STEREO EUVI/A, EUVI/B, and SDO/AIA disk images from April through August of 2012. For the automatically identified coronal holes we used the Active Contours Without Edges (ACWE) on EUV disk images. ACWE is an image segmentation technique that defines one or more contours by minimizing an energy function, which separates an image into foreground and background. When adapted to coronal hole segmentation, it produces a binary map of coronal holes in the original EUV image that is no longer defined by an intensity threshold. The ACWE results were then combined into global synchronic maps using a synchronic map generating algorithm. For the manually identified coronal holes, first an EUV global synchronic map was made using the same synchronic map generating algorithm. Then, a labeling software was used to carefully outline the boundaries of coronal holes identified by eye, resulting in a ground truth coronal hole map. Next, both the manual and automatically identified synchronic coronal hole maps were directly compared against each other and to a set of WSA model coronal hole predictions, where ADAPT photospheric magnetic field maps were used as input. This comparison was done quantitatively by calculating both the Jaccard index and the total predicted open area for each set of maps.