A Benchmarking of Learning Strategies for Pest Detection and Identification on Tomato Plants for Autonomous Scouting Robots Using Internal Databases

Table 3

Machine learning model features.

FEATURE	DEFINITION
Area	Area of the object.
Circularity	Shape factor for the circularity of an object. It calculates the similarity of the object with a circle.
Compactness	Compactness of the object.
Content Length	Total length of the object.
Convexity	Shape factor for the convexity of an object. The shape factor is one if the object is convex. If there are holes, the shape factor is smaller than one.
Rectangularity	It is considered as the shape factor for the rectangularity of an object.
Elliptic axis	Calculates the main and the secondary radius of the equivalent ellipse.
Phi orientation	The orientation of the equivalent ellipse.
Anisometry	The relationship between the main and the secondary radius of the equivalent ellipse.
Bulkiness	The relationship between the anisometry and the area of the object.
Structure factor	The relationship between the anisometry and the bulkiness.
Smallest circle	Determines the smallest surrounding circle of an object. It is the circle with the smallest area of all circles containing the object.
Inner circle	Calculates the largest inner circle of an object.
Inner rectangle	Determines the largest rectangle that fits into an object.
Roundness	Calculates the distance between the contour and the centre of the area.
Sides	The number of polygon sides.
Diameter	The maximum distance between two points of the object.
Orientation	Determines the orientation of the object.
Smallest rectangle	Calculates the rectangle with the smallest area of all rectangles containing the object.