  The integration of local elements into shape contours is critical for target
detection and identification in cluttered scenes. Previous studies have shown
that observers can learn to use image regularities for contour integration and
target identification. However, we still know little about the generalization
of perceptual learning in contour integration. Specifically, whether training
in contour detection task could transfer to untrained contour type, path or
orientation is still unclear. In a series of four experiments, human perceptual
learning in contour detection was studied using psychophysical methods. We
trained participants to detect contours in cluttered scenes over several days,
which resulted in a significant improvement in sensitivity to trained contour
type. This improved sensitivity was highly specific to contour type, but
transfer across changes in contour path and contour orientation. These results
suggest that short-term training improves the ability to integrate specific
types of contours by optimizing the ability of the visual system to extract
specific image regularities. The differential specificity and generalization
across different stimulus features may support the involvement of both
low-level and higher-level visual areas in perceptual learning in contour
detection. These findings provide further insights into understanding the
nature and the brain plasticity mechanism of contour integration learning.
