| dc.description.abstract | This paper evaluated some of the machine vision
techniques to extract fruits characteristic, which in this case is
Malang oranges. Appropriate algorithms are developed and
implemented to extract features from local fruit based on
Indonesian National Standard (SNI 3165: 2009) which is
concerning to oranges. The research is done by analyzing fruit
images, extracting HSV parameters and extracting feature
using contour detection, hull convex and RGB histogram. A
sensing machine which is consists of a photo box with a camera
and a conveyor has been developed. The detection process can
be done in real-time with the help of boxes equipped with
adequate lighting. Convex hull analysis can be used to
determine the diameter that has a great effect on the citrus
fruit classification. While the red-green ratio can be used to
label citrus fruits so that it can be used on a gradation-based
fruit sorting machine. The performance was evaluated in terms
of measurement accuracy which is above 88%. The research
has the potential to be improved with the addition of an
artificial intelligence-based decision system. | en_US |
