Image-based Agarwood Resinous Area Segmentation using Deep Learning

arXiv:2404.05129v1 Announce Type: new
Abstract: The manual extraction method of Agarwood resinous compound is laborious work, requires skilled workers, and is subject to human errors. Commercial Agarwood industries have been actively exploring using Computer Numerical Control (CNC) machines to replace human effort for this particular task. The CNC machine accepts a G-code script produced from a binary image in which the wood region that needs to be chiselled off is marked with (0, 0, 0) as its RGB value. Rather …

abstract arxiv code commercial computer control cs.cv deep learning errors extraction human image industries machine machines numerical segmentation skilled type work workers