radial-division


radial-division II (8987), vivera pigment print on MX1, stretched on a circular frame, 60 cm

radial-division II
is based on image color data, which is plotted on many different polar coordinate systems – radial bar charts.
all the color tables are aligned radially from the largest outer to the inner 0 chart ring with different start and end points.

i started out playing around with different data visualisations. soon i was more and more interested in again manipulating the rather technical output towards my idea of a abstract painting, a certain composition.
so the inherent data visualization function has been used without regard for its numerical output, but rather for the interplay of  colors and positions, which finally build up the image composition.

the latest works of this series–from 2018–are not on a circular board, but as seen here (still as mockup only), cut with laser along the outer fraying form, so that a more radiating impression is supported.

 

 

 

 

 

radial-division III.1 (strahlen), 2018

 

 

 

 

 

 

 

 

radial-division II.3, 2018

 

 

 

 

 

 

 

 

radial-division II, 2015-16

 

 

 

 

 

 

 

 

radial-division / data-disc 2, 2018

 

 

 

 

 

 

 

 

radial-division IV.1, 2017

 

 

 

 

curve drawer 1

__DRAW2_04-_60_4

 

schorfheide, 2010

 

the  curve drawer series is based on a vector curve function which reads out a color map or map array and draws in differently occillation structures over the stage, controlled by different mouse action.

 

 

 

 

swirl

V_Flower_PLUS_03-06

 

swirl series, 2009
based on a rotating bezier curve and color map read out.

 

 

 

 

de jong

 

de jong series, 2008

these works are based on the simple Peter de Jong map equations:
x’ = sin(a * y) – cos(b * x)
y’ = sin(c * x) – cos(d * y)

For most values of a,b,c and d the point (x,y) moves chaotically. The resulting image is a map of the probability that the point lies within the area represented by each pixel. As you let it render longer it collects more samples and this probability map and the image becomes more accurate.
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barnsley penrose

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spectr|a|um

spectraum01
spectr|a|um audio visual lounge
29. september 2007, Dexia Tower Brussels
LAB[au] and Dexia Tower invite:
Holger Lippmann (photos),  Limitatzero,  Olaf Bander