A Four Stage Image Processing Algorithm for Detecting and Counting of Bagworm, Metisa plana Walker (Lepidoptera: Psychidae)

• Published in: Agriculture (Basel) Vol. 11; no. 12; p. 1265
• Main Authors: Ahmad, Mohd Najib, Shariff, Abdul Rashid Mohamed, Aris, Ishak, Abdul Halin, Izhal
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2021
• Subjects: Algorithms; Artificial neural networks; bagworms; Cameras; Classification; Color; color features; Datasets; Deep learning; Defoliation; Economic impact; false color; faster R-CNN; Image processing; Image segmentation; Impact analysis; Insects; Larvae; Machine learning; Morphology; Motion detection; Motion perception; Neural networks; Object recognition; Petroleum industry; Pixels; Plantations; Pupae; Vegetable oils; Malaysia

The bagworm is a vicious leaf eating insect pest that threatens the oil palm plantations in Malaysia. The economic impact from defoliation of approximately 10% to 13% due to bagworm attack might cause about 33% to 40% yield loss over 2 years. Due to this, monitoring and detecting of bagworm populati...