Invariant recognition of natural objects in the presence of shadows

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.