Dual-Fusion Active Contour Model with Semantic Information for Saliency Target Extraction of Underwater Images

Abstract

Underwater vision research is the foundation of marine-related disciplines. The target contour extraction is significant for target tracking and visual information mining. Aiming to resolve the problem that conventional active contour models cannot effectively extract the contours of salient targets in underwater images, we propose a dual-fusion active contour model with semantic information. First, the saliency images are introduced as semantic information and salient target contours are extracted by fusing Chan–Vese and local binary fitting models. Then, the original underwater images are used to supplement the missing contour information by using the local image fitting. Compared with state-of-the-art contour extraction methods, our dual-fusion active contour model can effectively filter out background information and accurately extract salient target contours. Moreover, the proposed model achieves the best results in the quantitative comparison of MAE (mean absolute error), ER (error rate), and DR (detection rate) indicators and provides reliable prior knowledge for target tracking and visual information mining.

A Novel Adaptive Fractional Differential Active Contour Image Segmentation Method

“…where f 1 (x) and f 2 (x) are respectively the fitting mean of the local area inside and outside the contour curve of a given pixel point x, and the expression is Equation (9). K σ (x) is the Gaussian kernel function with standard deviation σ, I(y) is the intensity of the image I(x, y) at point y, φ(y) is the level set function at a point y, and δ(•) and H(•) are Equations ( 4) and (5).…”

“…The active contour model (ACM) [1] has the advantages of sub-pixel accuracy, topology adaptability, etc. Therefore, it has been widely used in the fields of image segmentation [2][3][4][5], video clipping [6,7], scene understanding [8], and object tracking [9,10]. Image segmentation based on ACM is a nonlinear segmentation method.…”