  We present an automated non-parametric light profile extraction pipeline
called AutoProf. All steps for extracting surface brightness (SB) profiles are
included in AutoProf, allowing streamlined analyses of galaxy images. AutoProf
improves upon previous non-parametric ellipse fitting implementations with
fit-stabilization procedures adapted from machine learning techniques.
Additional advanced analysis methods are included in the flexible pipeline for
the extraction of alternative brightness profiles (along radial or axial
slices), smooth axisymmetric models, and the implementation of decision trees
for arbitrarily complex pipelines. Detailed comparisons with widely used
photometry algorithms (photutils, XVISTA, and GALFIT) are presented. These
comparisons rely on a large collection of late-type galaxy images from the
PROBES survey. The direct comparison of SB profiles shows that AutoProf can
reliably extract fainter isophotes than other methods on the same images,
typically by >2 mag/arcsec^2. Contrasting non-parametric elliptical isophote
fitting with simple parametric models also shows that two-component fits (e.g.,
S\'ersic plus exponential) are insufficient to describe late-type galaxies with
high fidelity. It is established that elliptical isophote fitting, and in
particular AutoProf, is ideally suited for a broad range of automated isophotal
analysis tasks. AutoProf is freely available to the community at:
https://github.com/ConnorStoneAstro/AutoProf
