In this work, we investigate the use of a digital camera for colorimetry. O
ur system consists of a measurement device and a corresponding calibration
mapping. The goal is to design a system that will accurately assess the col
or of a sample. We develop two colorimetry systems by applying model-based
and regression-based techniques. For both systems, the measurement device i
s formed by a digital camera and a set of filters. The term multi-exposure
refers to the multiple snapshots taken by the camera along with filters. Th
e calibration mapping which consists of matrices then takes these filtered
camera RGB outputs, and returns the CIE XYZ tristimulus values under severa
l pre-selected illumination conditions. For the model-based system, a model
for the measurement device is employed; and our objective is to find the o
ptimal filters and the corresponding calibration sets that minimize a cost
function which accounts for errors in L*a*b* space, system robustness, and
filter smoothness. For the regression-based system, no modeling technique i
s applied to the measurement device. The objective is simply to find the op
timal calibration matrices that minimize the total least squared errors of
a given color set in CIE XYZ coordinates under several pre-selected illumin
ation conditions. We apply both types of colorimetry systems to two specifi
c tasks: general purpose measurement of color samples and colorimetry of hu
man teeth. We present experimental results for both applications. Finally,
in order to measure the parameters for these systems and evaluate their per
formance, we had to develop special instrumentation. We will briefly descri
be this effort as well.