Mentor/s
Mentor: Jason J. Molitierno, Ph.D. Course Instructor: Bernadette Boyle, Ph.D.
Participation Type
Paper Talk
Abstract
Image processing refers to a series of techniques that transform images, modify color tones, enhance features, and so on. Beyond image editing, these techniques play a crucial role in preprocessing for machine learning-based image recognition. This study explores the practical applications of linear algebra and statistics through two methods: Gaussian filtering and Principal Component Analysis (PCA). We specifically detail how Gaussian filters utilize linear transformations, combining linear algebra and statistics, to remove noise. PCA uses the statistical information of observed data to extract features that are less affected by noise while reducing data size.
College and Major available
Mathematics
Academic Level
Undergraduate student
Location
Session 4: Digital Commons & HC 106
Start Day/Time
4-23-2025 3:30 PM
End Day/Time
4-23-2025 4:45 PM
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Prize Categories
Best Multidisciplinary Research or Collaboration, Most Scholarly Impact or Potential, Best Writing
Image Processing: Gaussian Filtering and Principal Component Analysis
Session 4: Digital Commons & HC 106
Image processing refers to a series of techniques that transform images, modify color tones, enhance features, and so on. Beyond image editing, these techniques play a crucial role in preprocessing for machine learning-based image recognition. This study explores the practical applications of linear algebra and statistics through two methods: Gaussian filtering and Principal Component Analysis (PCA). We specifically detail how Gaussian filters utilize linear transformations, combining linear algebra and statistics, to remove noise. PCA uses the statistical information of observed data to extract features that are less affected by noise while reducing data size.
Students' Information
Yuna Ukawa, Computer Science and Mathematics Major, 2025