Abstract:
Computer vision as an object detection method can be used as a basis for automation
process of sorting and grading oil palm FFB (Fresh Fruit Bunches). Images
annotation are necessary to build datasets hence object detection model can identify
object features in images. This study aims to annotate multispectral images of oil
palm FFB with 2 categories, namely ripe and unripe FFB. Image acquisition is
carried out with LED-based multispectral imaging system. Annotation is done using
the python program application, called Labelimg. The number of annotated image
data is 60 images consist of 30 images of ripe FFB and 30 images of unripe FFB.
The results of annotation are .txt files contained information about bounding box
coordinate, class object, and image dimension.
