In this study, we construct Kantorovich variant of max-min kind operators,
which are nonlinear. By using these new operators, we obtain some uniform
approximation results in $N$-dimension ($Ngeq1$). Then, we estimate the error
with the help of H"{o}lder continuous functions and modulus of continuity.
Furthermore, we give some illustrative applications to verify our theory and
also investigate some shape-preserving properties of Kantorovich-type max-min
Bernstein operator. Lastly, we examine the image processing implementation of
our results via Kantorovich-type max-min Shepard operator.