An effective approach for visual saliency detection can help people search for the object of interest from vast visual information rapidly and accurately. Considering the complexity of noises covering a wide area in actual road images

we present a new pavement crack detection approach based on image saliency in this paper. This approach calculates the salient value of crack images in a coarse scale based on the grayscale sparsity and global contrast after grayscale correction on images

which are divided into small blocks. Then

according to the characteristics of the cracks

such as local brightness

edge

and continuity

we calculate the local saliency in the continuously outspread local neighbor domain in a fine scale. After enhancing the saliency based on the spatial continuity

we extract cracks using adaptive image segmentation method. A large number of experimental results demonstrate this approach can detect the crack areas more correctly and effectively compared with traditional methods. It better suppress noises

has lower missing rate and misuse detection rate. Moreover

the result is consistent with human visual characteristics.