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		<title>Texture Detection by Genetic Programming - Versionsgeschichte</title>
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		<title>Gbachelier: Die Seite wurde neu angelegt: „  == Reference == Mario Koeppen and Xiufen Liu: Texture Detection by Genetic Programming. Proceedings of the 2001 Congress on Evolutionary Computation CEC2001,…“</title>
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				<updated>2014-11-24T15:16:15Z</updated>
		
		<summary type="html">&lt;p&gt;Die Seite wurde neu angelegt: „  == Reference == Mario Koeppen and Xiufen Liu: Texture Detection by Genetic Programming. Proceedings of the 2001 Congress on Evolutionary Computation CEC2001,…“&lt;/p&gt;
&lt;p&gt;&lt;b&gt;Neue Seite&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&lt;br /&gt;
&lt;br /&gt;
== Reference ==&lt;br /&gt;
Mario Koeppen and Xiufen Liu: Texture Detection by Genetic Programming. Proceedings of the 2001 Congress on Evolutionary Computation CEC2001, pp. 867-872, IEEE Press, 27-30 May 2001. &lt;br /&gt;
&lt;br /&gt;
== DOI ==&lt;br /&gt;
http://dx.doi.org/10.1109/CEC.2001.934281&lt;br /&gt;
&lt;br /&gt;
== Abstract ==&lt;br /&gt;
This paper presents an approach to blind texture detection in images based on adaptation of the 2D-lookup algorithm by genetic programming. The task of blind texture detection is to separate textured regions of an image from non-textured (as e.g. homogeneous) ones, without any reference to a priori knowledge about image content. The 2D-lookup algorithm, which generalizes the well-known co-occurrence matrix approach of texture analysis, is based on two arbitrary image processing operations. By genetic programming, those image operations can be designed and adapted to a given recognition goal of the whole algorithm. The idea to employ such a framework for texture detection is to use a random image as adaptation goal. Despite of the fact that such a task has no exact solution, the system is able to fulfill this task to a certain degree. This degree is related to textureness in the image: the more texture, the higher the degree. The paper exemplifies this approach&lt;br /&gt;
&lt;br /&gt;
== Extended Abstract ==&lt;br /&gt;
&lt;br /&gt;
== Bibtex == &lt;br /&gt;
&lt;br /&gt;
== Used References ==&lt;br /&gt;
[1] Mario K ̈oppen and Javier Ruiz-del-Solar. Fuzzy-&lt;br /&gt;
based texture retrieval. In Proceedings FUZZ-IEEE’97,&lt;br /&gt;
Barcelona, Spain, pages 471–475, 1997.&lt;br /&gt;
&lt;br /&gt;
[2] Javier Ruiz-del-Solar and Mario K ̈oppen. Autopoiesis&lt;br /&gt;
and image processing II: Autopoietic-agents for texture&lt;br /&gt;
analysis. In Masoud Mohammadian, editor, Computa-&lt;br /&gt;
tional Intelligence for Modelling, Control &amp;amp; Automa-&lt;br /&gt;
tion, pages 72–76, Vienna, Austria, 1999.&lt;br /&gt;
&lt;br /&gt;
[3] Javier Ruiz-del-Solar, Patricio Parada, and Mario&lt;br /&gt;
K ̈oppen. Texture synthesis using soft-computing. In&lt;br /&gt;
Proceedings of the 4th Asian Fuzzy Systems Symposium,&lt;br /&gt;
pages 605–610, Tsukuba, Japan, 2000.&lt;br /&gt;
&lt;br /&gt;
[4] Andre Gagalowicz and Christine Graffigne. Blind tex-&lt;br /&gt;
ture segmentation. In Intenational Conference on Pat-&lt;br /&gt;
tern Recognition 1988, pages 46–50, 1988.&lt;br /&gt;
&lt;br /&gt;
[5] Roger W. Ehrich and Peichung F. Lai. Elements of a&lt;br /&gt;
structural model of texture. In Pattern Recognition and&lt;br /&gt;
Image Processing 1978, pages 319–326, 1978.&lt;br /&gt;
&lt;br /&gt;
[6] Robert M. Haralick. Statistical and structural approches&lt;br /&gt;
to texture. In Proc. of Int. Joint Conference on Pattern&lt;br /&gt;
Recognition, pages 45–69, 1979.&lt;br /&gt;
&lt;br /&gt;
[7] Fumiaki Tomita, Yochiaki Shirai, and Saburo Tsuji. De-&lt;br /&gt;
scription of textures by a structural analysis. IEEE&lt;br /&gt;
Trans. Pattern Analysis and Machine Intelligence,&lt;br /&gt;
(4)2:183–191, 1982.&lt;br /&gt;
&lt;br /&gt;
[8] R. Haralick, K. Shanmugam, and I. Dinstein. Textural&lt;br /&gt;
features for image classification. IEEE Transactions on&lt;br /&gt;
Systems, Man &amp;amp; Cybernetics, 3(6):610–621, 1973.&lt;br /&gt;
&lt;br /&gt;
[9] K. Franke and M. K ̈oppen. Towards an universal ap-&lt;br /&gt;
proach to background removal in images of bankchecks.&lt;br /&gt;
In Proceedings IWFHR’98, Taejon, Korea, pages 55–&lt;br /&gt;
66, 1998.&lt;br /&gt;
&lt;br /&gt;
[10] M. K ̈oppen, M. Teunis, and B. Nickolay. A framework&lt;br /&gt;
for the evolutionary generation of 2D-Lookup based&lt;br /&gt;
texture filters. In Proceedings IIZUKA’98, pages 965–&lt;br /&gt;
970, 1998.&lt;br /&gt;
&lt;br /&gt;
[11] M. K ̈oppen and S. Rudlof. Multiobjective optimiza-&lt;br /&gt;
tion by Nessy Algorithm. In P.K. Chawdhry R. Roy,&lt;br /&gt;
T. Furuhashi, editor, Advances in Soft Computing, pages&lt;br /&gt;
357–368, 1998.&lt;br /&gt;
&lt;br /&gt;
[12] Mario K ̈oppen, Achim Zentner, and Bertram Nickolay.&lt;br /&gt;
Deriving rules from evolutionary adapted texture filters&lt;br /&gt;
by neural networks. In 1999 IEEE International Fuzzy&lt;br /&gt;
Systems Conference Proceeding, volume 2, pages 785–&lt;br /&gt;
790, Seoul, Korea, 1999.&lt;br /&gt;
&lt;br /&gt;
[13] P.G. Anderson. The Unit RBF Network: Experiments&lt;br /&gt;
and preliminary results. In Proceedings NC’98, pages&lt;br /&gt;
292–297, 1998.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
== Links ==&lt;br /&gt;
=== Full Text === &lt;br /&gt;
http://science.mkoeppen.com/science/uploads/Publications/cec01.pdf&lt;br /&gt;
&lt;br /&gt;
[[intern file]]&lt;br /&gt;
&lt;br /&gt;
=== Sonstige Links ===&lt;/div&gt;</summary>
		<author><name>Gbachelier</name></author>	</entry>

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