Shadows are frequently present when we recognize natural objects, but it is
unclear whether they help or hinder recognition. Shadows could improve rec
ognition by providing information about illumination and 3-D surface shape,
or impair recognition by introducing spurious contours that are confused w
ith object boundaries. In three experiments, we explored the effect of shad
ows on recognition of natural objects. The stimuli were digitized photograp
hs of fruits and vegetables displayed with or without shadows. In experimen
t 1, we evaluated the effects of shadows, color, and image resolution on na
ming latency and accuracy. Performance was not affected by the presence of
shadows, even for gray-scale, blurry images, where shadows are difficult to
identify. In experiment 2, we explored recognition of two-tone images of t
he same objects. In these images, shadow edges are difficult to distinguish
from object and surface edges because all edges are defined by a luminance
boundary. Shadows impaired performance, but only in the early trials. In e
xperiment 3, we examined whether shadows have a stronger impact when exposu
re time is limited, allowing little time for processing shadows; no effect
of shadows was found. These studies show that recognition of natural object
s is highly invariant to the complex luminance patterns caused by shadows.