The invention relates to the field of
image segmentation, in particular to a self-adaptive
image segmentation method based on an Otsu method and a K-means method. According to the method, the
slack variable is introduced, the threshold value in the variable range is used as the local threshold value, the new threshold value search method is cyclically called by using the
queue, and the plurality of local optimal threshold values are quickly and adaptively obtained, so that the problem of high calculation complexity of a multi-threshold Otsu method in an existing adaptive K-means
image segmentation method is solved; the plurality of obtained thresholds are taken as the initial
centroid of the K-means method, and the number of iterations of the K-means method is reduced; and the threshold obtained by clustering through the K-means method is used as the
global optimal threshold, so that the image can be segmented accurately. According to the method, image illumination preprocessing servesas the purpose, the image can be segmented rapidly, accurately and adaptively, then the segmented area is corrected, and therefore information, lost due to illumination influence, of the image is recovered.