The visual simulation of the Anti-torpedo system is proposed for surface ships defend torpedo. The whole visual real-time process of the surface ships defend torpedo is expounded vividly. 3D models are created with software Multigen Creator. Driving framework programming with Vega Prime API can integrate 3D models, operation rules, special effect and whole scene to a platform system based on visual simulation. Torpedo target echo parameters are estimated accurately by real-time signal processing algorithms, and dynamic data is displayed in the scene of system. As a result, the system realizes real-time simulation of Anti-torpedo and performs well in system test.

Cloud gaming services are heavily dependent on the efficiency of real‐time video streaming technology owing to the limited bandwidths of wire or wireless networks through which consecutive frame images are delivered to gamers. Video compression algorithms typically take advantage of similarities among video frame images or in a single video frame image. This paper presents a method for computing and extracting both graphics information and an object's boundary from consecutive frame images of a game application. The method will allow video compression algorithms to determine the positions and sizes of similar image blocks, which in turn, will help achieve better video compression ratios. The proposed method can be easily implemented using function call interception, a programmable graphics pipeline, and off‐screen rendering. It is implemented using the most widely used Direct3D API and applied to a well‐known sample application to verify its feasibility and analyze its performance. The proposed method computes various kinds of graphics information with minimal overhead.

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This study introduces a graphical user interface (GUI) based on MATLAB to realize the automatic ex-traction of sizes of defects from the infrared sequence. To obtain the edge of the defect at deeper layer, a fusion stratagem of the maximum of gray values is adopted for an image subset in the sequence. Blob analysis to the fusion image is used to obtain the general information of defects of a specimen including the distributions and numbers of defects. The frame image is determined for a certain defect according to the peak of the time history curve of sensitive region variance. It can yield a region of interest (ROI) to expand the blob in the selected frame and the defect can be acquired by image segmentation. The results show that through this GUI, a better thermal image can be selected from a set of infrared sequence diagrams for quantitative extraction of different buried depth defect areas, which realizes automatic defect extraction, and its relative error is within 5%. The research on infrared automatic detection technology has certain significance.