I’m trying to recognize fruit types using a depth camera. For example, distinguish between bananas, apples and oranges. How should depth information be used without AI? Oranges and apples have similar colors, so I would like to use depth information.
what level of machine learning are you allowed to use for this assignment? why is this limited?
Machine learning can be used, but it is difficult because it requires learning cases in a short period of time.
and what would you get from the depth information ? size ? distance ?
i cannot see anything useful for recognition here
Isn’t depth information usually used when recognizing objects?
it can be, but usually not. the usual models just work with color pictures. color pictures are easy to get. depth information is rarely available.
Focus on capturing their 3D structure to analyze geometric properties like size, curvature, and volume. Develop specific depth profiles for each fruit type and use manual thresholding based on these metrics, combined with basic color analysis, for differentiation.
I can get the distance value for each pixel from the camera. Exactly what algorithm should be used to obtain object areas or features?
may be not,some picutres may be helpful