[Gzz-commits] gzz/Documentation/Manuscripts/Paper paper.tex

[Janne V. Kujala]

CVSROOT:        /cvsroot/gzz
Module name:    gzz
Changes by:     Janne V. Kujala <address@hidden>        02/11/20 05:01:28

Modified files:
        Documentation/Manuscripts/Paper: paper.tex 

Log message:
        the model

CVSWeb URLs:
http://savannah.gnu.org/cgi-bin/viewcvs/gzz/gzz/Documentation/Manuscripts/Paper/paper.tex.diff?tr1=1.44&tr2=1.45&r1=text&r2=text

Patches:
Index: gzz/Documentation/Manuscripts/Paper/paper.tex
diff -u gzz/Documentation/Manuscripts/Paper/paper.tex:1.44 
gzz/Documentation/Manuscripts/Paper/paper.tex:1.45
--- gzz/Documentation/Manuscripts/Paper/paper.tex:1.44  Wed Nov 20 02:41:04 2002
+++ gzz/Documentation/Manuscripts/Paper/paper.tex       Wed Nov 20 05:01:28 2002
@@ -189,19 +189,26 @@
 
 \section{Unique Textures}
 
-visually similar... easier to navigate if different textures
-context - fragment of PDF, location to which connected
+All PDF files look visually similar.
+It is easier to navigate if different textures are used as the background
+of a PDF document.
 
+context - fragment of PDF, location to which connected
 
 generating textures based on seed numbers [identity]
 
 distinguishability: should produce random vector in brain 
     (perception model in Fig.~\ref{fig-perceptual}) -- saving of bits
 
-visual cortex: image converted to Gabor-function basis;
-higher levels: local features combined to global perception,
-feature detectors ... contours ... shapes
-\cite{bruce96visualperception}
+The model:\\
+- visual cortex: image converted to Gabor-function basis (receptive fields)
+  \cite{bruce96visualperception} \\
+- higher levels: correlating local features combined to global perception, 
+  e.g. contours formed from consistent directions of adjacent receptive fields.
+  \\ 
+- feature detectors: different colors and certain shapes are recognized \\
+
+The ``intensities'' of the features produce a \emph{feature vector}.
 
 In \cite{schweitzer83texturing}, simple local features in artificial
 textures are used for implying global surface shape.
@@ -218,8 +225,12 @@
 
 The model explains easily why uniformly random texels (white noise)
 would not make easily distinguishable patterns: different instances
-of noise would all yield almost exactly the same pattern at
-the XXX
+of noise would all yield almost exactly the same 
+% pattern at the XXX
+feature vector:
+Noise has no global shape because there is no correlation between
+the random local features, it is simply perceived as the distribution
+of the local features (color and overall frequency (the size of texels)).
 
 Features independent at XXX should not correlate between XXX; for example,
 if all circles were green and all squares yellow, a considerable amount of