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In the era of big data, images and videos are one of the main means of information dissemination. In recent years, research on the problem of image and video reorganization and integration has become a hot topic in digital image processing technology. Using a computer for image processing, complicated programming is unavoidable. Therefore, it is necessary to optimize the interactive algorithms for image processing. In this paper, the content of image processing experiment is screened and integrated, and an image processing experiment system based on Matlab GUI platform is established for different levels of image processing knowledge modules. In order to verify the effectiveness and practicability of the optimization algorithm proposed in this paper, experimental simulations were performed on complex natural images and complex human eye images. The speed of the USB camera is generally between 15 frames/second and 25 frames/second, and in a 240 × 320 picture, the interactive algorithm in this article only needs about 59 ms, which is enough to complete the automatic interaction in the video in real time, which is convenient for subsequent image extraction. The experimental results show that the interactive algorithm in the complex image processing system in this paper optimizes the image extraction rate and improves the antinoise performance of the segmentation and the segmentation effect of the deep depression region.

Interactive Algorithms in Complex Image Processing Systems Based on Big Data