Histogramming: mapping of dataset (datafile) to histogram
W = HISTM(A,N)
C = HISTM(B,X)
For every object in the dataset B the set of feature values is mapped into a histogram, specifying for each bin the number of features having a value as specified for that bin. This is particular useful if the objects are images and the features are pixels. In that case for every image a histogram is found.
The dataset A may be used to find the proper histogram bins. In that case histograms with N bins are constructed between the minimum and maximum values over all objects in A.
Formally HISTM(,N) is an untrained mapping, to be trained by A as the dataset (datafile) A is used to determine the histogram bin centers. In case the bins are given like in HISTM(B,X) then we have a trained mapping. Consequently, if A is a datafile then in C = A*HISTM(A,10) all objects in A are processed twice. Once for determining the bin positions and once for filling them. If appropriate a command like C = A*HISTM(A(1,:),10) is thereby significantly faster, as it determines the bin positions by just a single object.
See IM_HIST for histogramming with known, fixed bin positions.