Author : Shannon Heh
Affiliation : Lynbrook High School San Jose, California
Country : USA
Category : Computer Science & Information Technology
Volume, Issue, Month, Year : 8, 6, April, 2018
Data collection is an essential, but manpower intensive procedure in ecological research. An algorithm was developed by the author which incorporated two important computer vision techniques to automate data cataloging for butterfly measurements. Optical Character Recognition is used for character recognition and Contour Detection is used for imageprocessing. Proper pre-processing is first done on the images to improve accuracy. Although there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify words of basic fonts. Contour detection is an advanced technique that can be utilized to measure an image. Shapes and mathematical calculations are crucial in determining the precise location of the points on which to draw the body and forewing lines of the butterfly. Overall, 92% accuracy were achieved by the program for the set of butterflies measured.
Keyword : Computer Vision, Image Recognition, Character Recognition, Ecology, Butterfly Cataloging
For More Details : https://airccj.org/CSCP/vol8/csit88606.pdf