Ruoyu Wang

Mentor: Dr. Benjamin Wilkinson
College of Agriculture and Life Science
"I became interested in science when I was a child. I was attracted by those amazing scientific phenomena introduced in a popular science book for children. Since then, being a scientist has become my dream. Getting involved with research at undergraduate level is such a good opportunity to develop the necessary qualities for future study and research. I will learn scientific attitude, scientific methods and scientific thinking in the research."




Electrical Engineering

Research Interests

  • Photogrammetry

Academic Awards

  • Certificate Authority Cup Mathematical Contest in Modeling Second Prize 2012
  • Certificate Authority Cup Mathematical Contest in Modeling Second Prize 2013
  • International Genetically Engineered Machine Contest Silver Prize 2014
  • University Scholars program 2015-2016


  • College Student Orchestra in Nanjing Agricultural University


  • N/A

Hobbies and Interests

  • Basketball
  • Violin
  • Fishing
  • Math

Research Description

Comparison of Two Feature-extraction Methods in Manual Mensuration
Photogrammetry is the science of rigorously determining the location and shape of objects using photographs. It is used in a wide range of applications such as agriculture, forestry, and engineering. There has been a recent influx of commercial software exploiting novel image registration (spatial alignment) procedures emerging from the computer vision field. An important part of image registration is detecting conjugate features in overlapping imagery. Although image matching is automated for many processing phases, manual mensuration is needed for registering specific features of interest. The current popular guidance for manual mensuration in modern systems has not been rigorously tested, and we believe these methods are significantly inadequate. Users are commonly instructed to select edges and corners of features for use in conjugation. However, depending on the modulation transfer of the imaging sensors (e.g. a digital camera), we conjecture that better choices are feature centroids and centerline intersections. We believe these are superior since they are easier to discriminate by the human eye than the exact location of edges and corners which are always blurred to some extent at high zoom levels. This project will focused on how the different manual mensuration schemes affect the propagated error in photogrammetric products.