VernierVision: Automatic Reading of Vernier Scales for Historic Observatory Telescopes
Date
2025-03-18
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
ORCID
0000-0001-5905-0422
Type
Thesis
Degree Level
Masters
Abstract
Advancements in deep space optics have revolutionized astronomical research, rendering older observa-
tory technologies obsolete. However, these historical resources still hold significant potential to inspire future
stargazers. Historic observatories, although outdated for contemporary research, are invaluable for students
and amateur astronomers constrained by the cost of modern equipment. This thesis aims to integrate elec-
tronic measurement systems into historical telescopes to enable remote and automated use while preserving
their original condition.
Specifically, the thesis focuses on the Observatory at the University of Saskatchewan, a landmark facility
that remains a landmark of substantial significance. Modernizing these telescopes without damaging their
irreplaceable components is crucial. Many historical telescopes use manual rotary Vernier scales to measure
direction, unlike modern telescopes with rotary encoders. The telescope in this study uses Vernier scales
for right ascension and declination measurements. Instead of replacing these scales, this thesis devises and
evaluates computer vision approaches to automatically read the original Vernier scales.
A computer vision system comprising cameras, object/line detection, and post-processing pipelines was
developed to automate scale measurements. The system unifies numeral localization and classification using
an object detection network and creates a robust post-processing pipeline for region-of-interest (ROI) and
feature extraction. The performance of the final system was sufficient for one of the two scales, however due
to additional sources of error, the performance on the second scale was lacking for high precision operation
Description
Keywords
Computer Vision
Citation
Degree
Master of Science (M.Sc.)
Department
Computer Science
Program
Computer Science