Abstract
Percentage of trash in the harvested sugarcane is one of the key quality indicators and needed to be examined since it affects sugar production efficiency. Currently, in Thailand, measurements of trash are done by randomly sampling by labors, which leads to delay and high labor cost this article aims to study the possibility of using the Principle Component Analysis (PCA) on the digital photos to detect harvested cane out of the trash. The component values of 5 color spaces (RGB, HSV, LAB, XYZ, and YIQ) of sugarcane stalks and trash images were obtained and then analyzed using PCA. The thresholding equation of each space was determined and applied for detecting sugarcane stalk pixel. The results revealed that the quality percentage (QP) of detection of all 5 color spaces was in a range from 82.27% to 96.19%, while those of LAB and RGB were the best at 96.06% and 94.90% respectively.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IOP Conference Series: Earth and Environmental Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
