Analyzing the Impact of Iridescence Strength on Animal Shape Recognition Using Computer Vision

Authors

  • Isabel Zhong Santa Clara High School
  • Kate Flowers Santa Clara High School

DOI:

https://doi.org/10.47611/jsrhs.v9i1.1161

Keywords:

Computer Vision, OpenCV, Iridescence, Animals and Insects, Shape recognition

Abstract

Iridescence, commonly found in nature, is the quality of a material to change colors depending on its interaction with light. For example, certain species of beetles distract predators with their iridescent exoskeletons that flash different colors depending on the angle the predator looks at them. Iridescent flowers, however, attract pollinators through their noticeable changes in color. Thus, it seems that iridescence can serve two contrasting purposes: concealment and attraction. The purpose of this project is to test whether different strengths in iridescence can impact its recognizability to animals and insects. 

Three different iridescent diffraction grating films were experimented with: 500 lines/mm, 532 lines/mm, and 1000 lines/mm. Matte paper was used as a control. Four circular epoxy resin disks (8 cm diameter) and four square epoxy resin disks (7 cm side length) were created. Each diffraction grating film type and the matte paper was glued onto one disk of each shape. Photos of each disk were then taken at angles of 30, 45, 60, and 90 degrees in a photo booth and processed through a computer vision algorithm, the Ramer-Douglas-Peucker algorithm, to perform contour approximation.

The results gathered cannot conclude that the strengths of iridescence have an impact on shape recognition and detectability due to limitations and potential errors. Nonetheless, the study can suggest that the specific usage of the Ramer-Douglas-Peucker algorithm for edge and area detection through OpenCV (an open-source computer vision library) is inadequate in imitating animal and insect visual systems when analyzing iridescence.

Downloads

Download data is not yet available.

Published

09-15-2020

How to Cite

Zhong, I., & Flowers, K. (2020). Analyzing the Impact of Iridescence Strength on Animal Shape Recognition Using Computer Vision. Journal of Student Research, 9(1). https://doi.org/10.47611/jsrhs.v9i1.1161

Issue

Section

AP Research Articles