Woolz Image Processing  Version 1.7.5
WlzCelCmpFeatures
Name
WlzCelCmpFeatures - computes the features of cells within clumps.
Synopsis
WlzCelCmpFeatures [-b] [-c<col 0>[,<col 1>[,col 2]]] [-C] [-d<debug mask>]
[-f<input image format>] [-h]
[-l<col 0>[,<col 1>[,<col 2>]]] [-L] [-n#]
[-o<out file>] [-s<seg file base>]
[-S<seg file format>] [-v] [<input image>]

Options
 -b Treats the segmented cells and clumps as binary objects, ignoring their image values. -c Colour space for segmenting the cells. The colour is specified by a single letter which is one of - red, green, blue, yellow, magenta, cyan, hue, saturation, value and grey. All processing is done on single (grey) valued images. Two methods may be used to get the grey valued image from the input image: If one colour is specified then that colour space is used to construct a grey valued image, if a colour pair is given then the ratio of the first to second is used, alternatively if a colour triple is given the first two are used for the ratio and the third as a multiplier. See WlzRGBChannelRatio(1). -C Invert cell image values. -d Probably only useful for debugging, this is a bit mask which controls the debug output. Mask bit 1 set for text output and mask bit 2 set for object output. The default is no debug output. -f Input image format. -h Help - prints a usage message. -l Colour space for segmenting the clumps. The colour is specified by a single letter as for the cells segmentation. -L Invert clump image values. -n Number of angular increments to use (default 360). -o Output file for the feature values. -s The segmentation output image base is used to provide a colorised image showing the segmentation for each segmented clump. Unless a file base is given no segmentation images are output. -S Output colorised image format. -v Verbose output.
Description
Extracts domains for clumps and cells within clumps, both from within the given image. The cells and clumps are used to compute numerical features which are output to the given file. Colorised images showing the segmentation may also be output if required. The features computed are: The ratio of cell / clump areas. The ratio of clump minimum to maximum diameter. The centrality of the cells with respect to the clump, with the centrality

$c = \frac{\sum_{i,j}{m_{i,j}(R_i - r_{i,j})}} {\sum_{i,j}{m_{i,j}R}}$

The image formats recognised are: jpg, tif and wlz. By default the image is read from the standard input and the features are output to the stanard output.
Example
WlzCelCmpCentrality -b -c b,r -l r,g -s image-seg-.jpg -v image.jpg

Reads an image from the file image.jpg. Segments clumps using the ratio of red to green and cells using the ratio of blue to red. For each clump an colorised image showing the segmentation is output to files image-seg-000000.jpg, image-seg-000001.jpg, .... The numerical features are preceded by column labels and output to the standard output.
File
WlzCelCmpFeatures.c