From Pherographia To Color Pherographia

From Pherographia to Color Pherographia ColorSketchingwith Artificial Ants
C.M. Fernandes12
C. Isidoro2
F. Barata2
J.J. Merelo1
A.C. Rosa2
1University of Granada
2Technical UniversityofLisbon

Summary
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Original b/w photo
Pheromonedensityafter 100 iterations
Antsafter 100 iterations
The Ant System: from Chialvo and Millonas’s Ant Model to Pherographia.
Artwork created with monochromatic pherographia.
Color Pherographia (four variations).
Results.
Conclusions and future work.
CongressonEvolutionaryComputation, CEC’11, NewOrleans, USA, 2011

The Original Model
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Dante Chialvo and Mark Millonas, How Ants Build Cognitive Maps, 1995
The model simulates a swarm of ants moving in an homogeneous environment.
A population of ants is randomly distributed in a two-dimensional array.
The ants move one step (cell) in each iteration, following simple rules.
Global and complex behaviour emerges from the simple rules and from the indirect interaction of the ants via the environment.
Self-Organization
Stigmergy
Simple ((local, no explicit memory, homogeneous and isotropic)

The Original Model (Chialvo and Milonas)
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Evaporation: pheromonedensityineachcellisdecreasedby a constantamount.
Pheromonedeposition rate: T= η
increasingthecell’spheromonedensity σ
Pheromone weighting function:
β: degree of randomnesswithwhichtheantsfollowthepheromonegradient
δ: saturationeffect, ant’sabilitytosensepheromonedecreases at highconcentrations
Normalised Transition probabilities (probability to go from cell k to cell i)
w = 1/20
w = 1/12
w = 1/12
w = 1/4
w = 1/4
w = 1/2
w = 1/2
w = 1

The Original Model
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Ramos and Almeida’s Model
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Ramos and Almeida, Artificial AntColoniesin Digital Images Habitat, ANTS 2000
- Instead of constant pheromone deposition rate, a term not constant is included:
Constant
Gives a measure of similarity
between two different lattice
windows, in terms of grey level
spatial arrangement.

Final Model
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Fernandes, Ramos and Rosa, Self-Regulated Artificial AntColonieson Digital Image Habitats, InternationalJournalof Lateral Computing, 2005
An “evolutionary” component is added to the ant system.
Each ants has an initial energy that decreases in each time step: the probability of surviving depends on the energy: P = 1-e(a)
Each ant is allowed to reproduce in each time step. The reproduction probability depends on the number of neighbouring ants and the pheromone density.
W(0) = W(8) =0;
W(4) = 1;
W(5) = W(3) =0.75;
W(6) = W(2) =0.5;
W(7) = W(1) = 0.25.

Timor Mortis Conturbat Me (2008)
“Timor Mortis...” was exhibited at the P4Photography art gallery, in Lisbon.
About this work: http://carlosmfernandes.com/index_archivos/Page768.htm
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EadweardMuybridge(1830-1904)
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The Horse and the Ants (2009)
The Horse and the Ants has been exhibited in several art and science shows.
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Criatividade Computacional, ISCTE, Abril de 2010
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Studies for a Modern Zoetrope (2011)
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Becher’s typologies: analysis and synthesis
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Bernd e HillaBecher
Idris Kahn

Becher’stipologies: analysis and synthesis
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ColorPherography
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The main difference is the equation:
In b/w pherography, ∆ measuresthecontrastintheregionaroundtheant’sposition.
In colorpherography:
First, RBG isconverted to L, a and b (Labcolorspace)
L measuresthelightness
a and b measurethecolor.
∆ istheEuclideandistancebetweentheaverageof L, a and b, eachaveragedoverthecellandits 8 neighborigcells, andtheaverageof L, a and b averagedoverthepreviouscellandits 8 neighboringcells.

ColorPherography
Four variations were tested, each one with different rules for the ants movements and for handling occupied cells
Originally, the objective was to remove a bias introduced by constraint of having no more than one ant in each cell.
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ColorPherography
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Variation 1: when an ant tries to move to an occupied cell, the ant that occupies that cell is moved in the same direction and its directional vector changes.

ColorPherography
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Variation 2: the ants are not allowed to move to occupied cells. If one tries to move to an occupied cell, it will stop, and the direction of the ant occupying that cell changes to that of the vectorial sum between the original direction and the one towards which this ant tried to move.

ColorPherography
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Variation 3: ants “bounce off” if they try to move to occupied cells.

ColorPherography
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Variation 4: introduces speed and implements ants with variable speed, that is, the speed may change when an ant moves to a cell occupied by another ant.

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Conclusions and Future Work
The monochromatic pherographia has been extended to colorpherographia.
Colorpherographia also detects the edges of the image.
Investigate other local and simple rules that generate different global behaviour.
Emergence, memory and readaptation (videos).
Implement pherographia (B/W and color) in a digital camera using LUA programming language.
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From Pherographia To Color Pherographia

by Carlos M. Fernandes on Jun 28, 2011

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From Pherographia To Color Pherographia — Presentation Transcript