Unsupervised texture based image segmentation by simulated annealing using Markov random field and Potts models

Goktepe, M
Atalay, Mehmet Volkan
Yalabik, N
Yalabik, C
Unsupervised segmentation of images which are composed of various textures is investigated A coarse segmentation is achieved through a hierarchical self organizing map. This initial segmentation result is fed into a simulated annealing algorithm in which region and texture parameters are estimated using maximum likelihood technique. Region geometries are modeled as Potts model while textures are modeled as Markov random fields. Tests are performed an artificial textured images.
14th International Conference on Pattern Recognition


Unsupervised segmentation of gray level Markov model textures with hierarchical self organizing maps
Goktepe, Mesut; Yalabik, Nese; Atalay, Mehmet Volkan (1996-01-01)
Segmentation of gray level images into regions of uniform texture is investigated. An unsupervised approach through the use of Kohonen's self organizing map (SOM) and a multilayer version of it, the hierarchical self organizing map (HSOM), is employed to find the regions in an image composed of textures from different classes. For testing, gray level artificial textured images modeled as Markov random fields are used as the input. No parameter estimation is done. The size and the topology of SOM and HSOM ar...
Unstructured grid generation and a simple triangulation algorithm for arbitrary 2-D geometries using object oriented programming
Karamete, BK; Tokdemir, Turgut; Ger, M (Wiley, 1997-01-30)
This paper describes the logic of a dynamic algorithm for a general 2D Delaunay triangulation of arbitrarily prescribed interior and boundary nodes. The complexity of the geometry is completely arbitrary. The scheme is free of specific restrictions on the input of the geometrical data. The scheme generates triangles whose associated circumcircles contain 'no nodal points except their vertices. There is no predefined limit for the number of points and the boundaries. The direction of generation of the triang...
Unequal error protection of SPIHT encoded image bit streams
Alatan, Abdullah Aydın; Akansu, A.N. (Institute of Electrical and Electronics Engineers (IEEE), 2000-6)
A derivative of the Set Partitioning into Hierarchical Trees (SPIHT) image coding method, which generates substreams with different error-resilience properties, is proposed. By dividing the image bit stream into three classes, substreams with different immunity properties are obtained. The unequal protection of these substreams with different channel coding rates improves the overall performance of the method against channel errors. Simulation results show the superiority of the proposed method over some of...
Parametric Design in Urbanism: A Critical Reflection
Çalışkan, Olgu (2017-01-01)
Parametric modelling run by the explicitly defined algorithms generating synchronically auditable dynamic forms and patterns, has become a prominent method especially in architecture. Though the use of parametric models has got wider in urban design, the critical reflection on the actual and possible application of the method in urbanism has fallen limited so far. The paper tends to relate parametric design with the contemporary understanding of urbanism with regards to the idea of design control in the the...
Unsupervised Electromagnetic Target Classification by Self-organizing Map Type Clustering
Katilmis, T. T.; Ekmekci, E.; Sayan, Gönül (2010-07-08)
In this study, design of a completely unsupervised electromagnetic target classifier will be described based on the use of Self-Organizing Map (SOM) type artificial neural network training and Wigner distribution (WD) based target feature extraction technique. The suggested classification method will be demonstrated for a target library of four dielectric spheres which have exactly the same size but slightly different permittivity values.
Citation Formats
M. Goktepe, M. V. Atalay, N. Yalabik, and C. Yalabik, “Unsupervised texture based image segmentation by simulated annealing using Markov random field and Potts models,” presented at the 14th International Conference on Pattern Recognition, Brisbane, AUSTRALIA, 1998, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55752.