Research Article
A Combined Approach on RBC Image Segmentation through Shape Feature Extraction
Algorithm 3
Algorithm of multiscale segmentation through mapped depth.
1. Initialization | 1.1 Get the whole depth map image from the output of shape from shading procedure; | 1.2 Obtaining the range image by filling the value of each pixel, which is associated with the | current processing cell by depth data; | 1.3 Compute an estimate of the noise variance at each pixel; | 1.4 Computing mean curvature and Gaussian curvature through separable convolution; | 1.5 Computing the surface type label image and find all connected components of each surface | type label image, sort it to get histogram distribution; | 1.6 Extracted seed region through erosion (contraction) operation. | 2. Iterative variable order surface fitting | 2.1 Perform surface fit from the lowest order, if it is OK using RMS error and region test; | 2.2 Then goto 3; | 2.3 Else increase the order and fit again; | 2.4 if order >4, then return. | 3. Region Growing | 3.1 Find the new region consisting of compatible connected neighboring pixels. |
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