Viability of Computer Vision in Apple Starch Analysis
Document Type
Creative works or constructive object presentation
Campus where you would like to present
Ellensburg
Event Website
https://digitalcommons.cwu.edu/source
Start Date
18-5-2020
Abstract
Quality control in the agriculture industry is universally used by production facilities but remains almost unseen by the consumer unless it is done wrong, in which case it can be glaringly obvious. It is for this reason that QC programs should be meticulously structured to catch potential problem products before they are processed. Currently a vast majority of QC lab work is made from human observation, which leads to large variance in data due to human bias and error. With increasing strides in efficiency and accessibility in the field of computer vision, it is essential for companies to implement computer vision in their QC programs.The purpose of the Apple Starch Analyzer is to provide a simple to use and robust solution for detecting the starch contents of apples, a process commonly used in apple QC for any warehouse. This project shows viability and concept and could serve as a starting point for widespread adoption of computer vision in agricultural QC labs, saving companies money and prevent logistical complications before products even reach the packing and shipping floors.
Recommended Citation
Rath, Caleb, "Viability of Computer Vision in Apple Starch Analysis" (2020). Symposium Of University Research and Creative Expression (SOURCE). 43.
https://digitalcommons.cwu.edu/source/2020/CEPS/43
Department/Program
Engineering, Technologies, Safety & Construction
Additional Mentoring Department
https://cwu.studentopportunitycenter.com/2020/04/viability-of-computer-vision-in-apple-starch-analysis/
Viability of Computer Vision in Apple Starch Analysis
Ellensburg
Quality control in the agriculture industry is universally used by production facilities but remains almost unseen by the consumer unless it is done wrong, in which case it can be glaringly obvious. It is for this reason that QC programs should be meticulously structured to catch potential problem products before they are processed. Currently a vast majority of QC lab work is made from human observation, which leads to large variance in data due to human bias and error. With increasing strides in efficiency and accessibility in the field of computer vision, it is essential for companies to implement computer vision in their QC programs.The purpose of the Apple Starch Analyzer is to provide a simple to use and robust solution for detecting the starch contents of apples, a process commonly used in apple QC for any warehouse. This project shows viability and concept and could serve as a starting point for widespread adoption of computer vision in agricultural QC labs, saving companies money and prevent logistical complications before products even reach the packing and shipping floors.
https://digitalcommons.cwu.edu/source/2020/CEPS/43
Faculty Mentor(s)
Lad Holden