An Automatic Framework for Embryonic Localization Using Edges in a Scale Space

<p>Localization of Drosophila embryos in images is a fundamental step in an automatic computational system for the exploration of gene-gene interaction on Drosophila. Contour extraction of embryonic images is challenging due to many variations in embryonic images. In the thesis work, we develop a localization framework based on the analysis of connected components of edge pixels in a scale space. We propose criteria to select optimal scales for embryonic localization. Furthermore, we propose a scale mapping strategy to compress the range of a scale space in order to improve the efficiency of the localization framework. The effectiveness of the proposed framework and the scale mapping strategy are validated in our experiments.</p>

Name thesis:degree_name

Master of Science

Discipline thesis:degree_discipline

Department of Computer Science

Year

2013

Author dc:creator

• Bessinger, Zachary

Contributors dc:contributor

• Qi Li (Director), Guangming Xing, James Gary

• Drosophila
• Canny
• Gaussian
• Gaussian Processes
• Contour Extraction
• Connected Components
• Computing Methodologies
• Systems Engineering
• Machine Learning
• Computer Sciences
• Entomology
• Genetics
• Software Engineering

Repository record dc:identifier

https://digitalcommons.wku.edu/theses/1262

OAI identifier oai:identifier

oai:digitalcommons.wku.edu:theses-2265