Humanoid-Eye Imaging System Model with Ability of Resolving Power Computing - Advances in Image and Graphics Technologies - page 101

non-ideality. The error is at most half a pixel in situation that one edge of a LED's
image falls around the center of a pixel and two LEDs' images will form an error of
one pixel together at most.
Reviewing all the results, the experiment demonstrates nearly 98% images in favor
of the MDD prediction and strongly supports the formula for both of ARP and MDD
we achieve in chapter 3.

5 Conclusions

This paper abstracts two equivalent models of human eyes' imaging and photo-
sensing parts, and then constructs HIS, an innovative imaging system which integrates
main features of human eyes and many other practical imaging systems. We derive
criteria of point-distinguishability for HIS and define its resolving power by Ray-
leigh's law and theory of receptors, which restrict the resolving power of HIS. By
these criteria and definition, we propose two sets of formulas for ARP and MDD cal-
culation, involving feature parameters of HIS and object points' variables. The expe-
riment result shows that predictions of the resolving power calculation formulas for
HIS are congruous with reality, with nearly 98% correct ratio. We have successfully
simulated HIS and integrated the formulas of its resolving power in a multi-resolution
object 3D models recognition computer program. The results provide supports for
outstanding efficiency and applicability of HIS and relevant resolving power calcula-
tion in 3D mesh management. Future work includes evaluation of other factors related
to resolving power of HIS and further application in computer.

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