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

Underwater vision research is the foundation of marine-related disciplines. The target contour extraction is of great significance to target tracking and visual information mining. Aiming at 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 extract salient target contours 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.

A novel detection of weld defects by magneto-optical imaging under combined magnetic field

To overcome the shortcomings of existing magneto-optical imaging, such as the saturation of an image under a constant magnetic field and the ambiguity of an image under an alternating magnetic field, imaging using a combined magnetic field is presented in this research. Weld defect samples include a laser-cut groove, a wire-cut penetrating groove, a pit and a Z-shaped crack. Magneto-optical imaging experiments were carried out under different magnetic fields. Contour extraction and standard deviation calculations were carried out for all magneto-optical images and the maximum standard deviation of the laser-cut groove under an alternating magnetic field was 20.9, which was less than the maximum value of 37.4 under a combined magnetic field. The experimental results show that the contrast of a magneto-optical image obtained under the combined magnetic field is greater than that obtained under the alternating magnetic field for all defects. The proposed combined magnetic field could optimise the magneto-optical imaging effect for weld defects under the existing excitation method to a certain extent.

A Motion Image Pose Contour Extraction Method Based on B-Spline Wavelet

In order to improve the accuracy of traditional motion image pose contour extraction and shorten the extraction time, a motion image pose contour extraction method based on B-spline wavelet is proposed. Moving images are acquired through the visual system, the information fusion process is used to perform statistical analysis on the images containing motion information, the location of the motion area is determined, convolutional neural network technology is used to preprocess the initial motion image pose contour, and B-spline wavelet theory is used. The preprocessed motion image pose contour is detected, combined with the heuristic search method to obtain the pose contour points, and the motion image pose contour extraction is completed. The simulation results show that the proposed method has higher accuracy and shorter extraction time in extracting motion image pose contours.