Thresholding (Iterative Method)
Thresholding is inevitably one of the mostly used image processing algorithm. It is told as the simplest method of image segmentation. In this post, I want to introduce one thresholding algorithm that is powerful enough yet simple enough to implement. The method called "Iterative Method." Below is the step by step used in the algorithm: An initial threshold (T) is chosen, this can be done randomly or according to any other method desired. The image is segmented into object and background pixels as described above, creating two sets: G 1 = {f(m,n):f(m,n)>T} (object pixels) G 2 = {f(m,n):f(m,n) T} (background pixels) (note, f(m,n) is the value of the pixel located in the m t h column, n t h row) The average of each set is computed. m 1 = average value of G 1 m 2 = average value of G 2 A new threshold is created that is the average of m 1 and m 2 T’ = ( m 1 + m 2 )/2 Go back to ...