Marker-Controlled Watershed Segmentation The watershed transform is often applied to separating touching objects in an image problem. The watershed transform finds "catchment basins" and "watershed ridge lines" in an image by treating it as a surface where light pixels are high and dark pixels are low. The watershed transform works better if you can identify, or "mark," foreground objects and background locations
(1)Bright pixels, pixels region with high intensity. (2)Dark-center pixels, pixels with low intensity fully surrounded by bright pixels (3)Dark pixels,, pixels with low intensity partially surrounded by bright pixels 3 types of pixels
4 types of cell (1)Bright pixels represent type I cells and boundary. (2)Dark-center pixels for type II cells (3)Dark pixels for both type III (darker none circular cell )and type IV (apoptosis)
Otsu thresholding with Sobel operator In order to apply a Otsu thresholding to obtain all the foreground, yet the dark pixels would not get lost. With a Sobel operator The gradient has been take into consideration. Dark pixels regions is defined as intensity smaller than the Threshold of Otsu and larger than k ・ t sobel
Noise and artifacts elimination 1.Eliminate narrow dark pixel regions around the boundary. 2.Majority filter 3.Fill holes under certain area 4.Erase dark pixel region without any bright pixel
Majority filter The Majority Filter tool has two criteria to satisfy before a replacement can occur: the number of neighboring cells of a similar value must be large enough (Majority or Half), and those cells must be contiguous about the center of the filter kernel. The second criteria concerning the spatial connectivity of the cells minimizes the corruption of cellular spatial patterns.
Smart marker extraction For dark pixels and dark-center pixels
Smart marker extraction For Bright pixels 1.Dilate to get rid of the boundary 2.A bright pixel cell has a circle area beyond a threshold