Switching filtering method for interactive systems

Abstract

Aiming at the problem that the mixed noise interference caused by the mixed projection noise system is not accurate and the real-time performance is poor, this article proposes an adaptive system switching filtering method based on Bayesian estimation switching rules. The method chooses joint bilateral filtering and improved adaptive median filtering as the filtering subsystems and selects the sub-filtering system suitable for the noise by switching rules to achieve the purpose of effectively removing noise. The simulation experiment was carried out by the self-developed human–computer interactive projection image system platform. Through the subjective evaluation, objective evaluation, and running time comparison analysis, a better filtering effect was achieved, and the balance between the filtering precision and the real-time performance of the interactive system was well obtained. Therefore, the proposed method can be widely applied to various human–computer interactive image filtering systems.

Contactless interactive control technology with a switching system based on Butterworth filter and modified strong tracking Kalman filter

“…Namely, sensors obtain the peripheral 2D (two-dimensional) or 3D (three-dimensional) gesture information, and then the data processing algorithms are used to analyze, extract, and recognize the gestures to obtain accurate gesture interaction position coordinates. 5 However, image filtering is an important part of gesture image recognition, and thus, it has been widely studied. [6][7][8] Klosowski and Frahm 9 proposed a real-time image noise filter suitable for the MRI (magnetic resonance imaging), which can effectively remove the background noise.…”