Yes, those are good and there are many more dealing with these issues. E.g.
A Note on the Measurements of Quantized Areas and Boundaries
University of Maryland, Computer Science Center (November 1978) TR-713
Rosen D. On the areas and boundaries of quantized objects
Computer Graphics and Image Processing
Volume 13, Issue 1, May 1980, Pages 94-98
Area and perimeter measurement of blobs in discrete binary pictures
Computer Graphics Image Processing, 6 (1977), pp. 434–451
P.V Sankar, E.V Krishnamurthy
On the compactness of subsets of digital pictures
Computer Graphics Image Processing, 8 (1978), pp. 136–143
Grid intersect quantization schemes for solid object digitization
Computer Graphics Image Processing, 8 (1978), pp. 25–42
Compact figures in digital pictures
IEEE Trans. Systems Man. Cybernet., SMC-4 (1974), pp. 221–223
T.J Ellis, D Proffitt, D Rosen, W Rutkowski
Measurement of the lenths of digitized curved lines
Computer Graphics Image Processing, 10 (1979), pp. 333–347
plus the papers dealing with Bresenham circle and line algorithms.
My take is that it is best to use 8 neighbours connectivity (smallest error without having to resort to some length and area correction factors that might not always apply) for the foreground and centre the ROIs on the pixels, not in the top left corner as traditionally IJ does as this tends to confuse what one is measuring. (No, I am not suggesting to change how IJ does it now, but it is useful to think it that way, Particles8 and Lines8 are based on this to compute areas and lengths).
My other suggestion is when dealing with areas, count both the the enclosed polygon area (via the Green/Pick method) and the number of pixels in the object (what IJ does, but this overestimates area). The two will not be the same, and provide different information.
This was briefly discussed in the github link above.