Seales, William


PI: Brent Seales

 

Digital Restoration

Recovering lost text from ancient or damaged manuscripts using non-invasive imaging and computation.

 

Computational Methods

We are using our Volume Cartographer library ((C++)) for the analysis of 3D volumetric CT data. Additionally, we are using ((Python)) and ((Tensorflow)) for further processing so that we can segment and classify writing surfaces and ink from a CT scan.

 

Project Members

Seth Parker (CS/Vis Center, UK CS Grad Student)

Stephen Parsons (CS/Vis Center)

Kyra Seevers

Daniel B Dopp, Dept of Marketing and Supply Chain

Ankan Bhattacharyya, Graduate, Added on LCC resources on 06/22/2022 

Shunnan Chen, Added on LCC resources on 11/15/2022 

 

Software Used:

Python

Tensorflow

GPUs

Insight Segmentation and Registration Toolkit (ITK)

Gemini Storage

 

Funding

Funding is provided through the Digital Restoration Initiative.

 

Publications (resulting from DLX usage):

None



Staff

Mami Hayashida (Research Computing Infrastructure, Digital Restoration Initiative) [mhaya2@uky.edu

Center for Computational Sciences