Evolutionary Clustering in Indonesian Ethnic Textile Motifs

box-count Batik Gurdha (Jawa)

Figure 1

The box-count fractal dimension calculation for Batik Gurdha

The second parameter is related to the chosen color used to present the motif. The histogram of
each color in a digital image contains a lot of information related to the mixture of the colors used in
it. An example is shown in figure 2 on the motif of Sasirangan in textiles from South Kalimantan.
Here we can see that a color histogram is a vector stores the number of a given color in an image
(Pass, et. al, 1996). Revealing the color histogram of a digital image is by means of retrieving the
computational information in an image from the bottom-up. Thus, in the sense of memeplexes, this
is an elementary information reflected from an image and a thing that is reflecting the thing that it is
in mind as transformed onto the artifact.

It is also worth noting that color histograms are very sensitive to the brightness of the image. Thus
before the analysis, we should standardized the vector by using histogram equalization (Acharya &
Ray, 2005). If we denote the histogram of the a single color, H ^R,G,B (w), then we could apply the
equalization from its cumulative distribution function,

x

CR,G,B(x)_=∑HR,G,B(w)
w=0

This cumulative distribution function is being normalized to have more gradual cumulative
distribution function by applying,

w = CWG^jB ( x )t

l×h

where, C_w^R,G,B ( x) is the value of cumulative distribution in w- degree of the Red, Green, and Blue
gradation, t as the threshold of respective color degree, and l×hare the dimension of the image. In
fact, most of image processing software has included this function in their package. Thus, the point is
to make sure that our images of motif are not too dark or too bright before the construction of the
memeplex.

From the two distinctive categories we can fill the memeplexes as we could reveal from a lot of
Indonesian traditional motifs,

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