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Otsu algorithm based on adaptive Kalman filter

Aiming at the problem that the traditional Otsu algorithm cannot segment the image well under the condition of illumination and background interference and the traditional Kalman filter performs poorly in predicting the position of nonlinear targets, an Otsu algorithm based on adaptive Kalman filter is proposed. In this algorithm, the Kalman gain is adjusted online to make the filter quickly and smoothly predict the trajectory of nonlinear targets accurately, and the area of background and shadow area is reduced by setting the focus area. At the same time, in order to reduce the area of the focus area and ensure that the target is always in the region, the focus area is placed in the target position predicted by the adaptive Kalman filter. The experimental results show that compared with the traditional algorithm, the image segmentation performance of this algorithm is significantly improved.