Article,
An Efficient Salient Region Detection on Underwater Image with Grabcut Algorithm
International Journal of Innovative Science and Modern Engineering (IJISME), 4 (11): 1-5 (June 2017)
Abstract
Saliency detection aims at automatically estimating visually salient object regions in an image, saliency segmentation and foreground extraction are two important applications of this. However, it is a challenge for underwater images to estimate salient regions by saliency detection methods because of the low-contrast and poor quality. In this paper, we address this problem by combining the detected object regions rather than the whole image, where Sobel edge detector and Active contour is used for proposing candidate regions. We extensively evaluated our method on underwater images, and experimental results show that the performances of saliency detection and segmentation are improved. These saliency segmentation masks are further used to extract the foreground objects of an image.
