Genetic adaptation of segmentation parameters

Lecture Notes in Geoinformation and Cartography

Volumn 0, Issue 9783540770572, 2008, Pages 679-695

  Costa, G A O P ^a   Feitosa, R Q ^a,b   Cazes, T B ^a   Feijo B ^a  

^a PONTIFICAL CATHOLIC UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^b STATE UNIVERSITY OF RIO DE JANEIRO   (Brazil)

Author keywords

Genetic algorithm; Object based classification; Optimization

Indexed keywords

IMAGE SEGMENTATION; OPTIMIZATION; REMOTE SENSING;

AUTOMATIC ADAPTATION; FITNESS FUNCTIONS; HIGH SPATIAL RESOLUTION; IDEAL SOLUTIONS; OBJECT-BASED CLASSIFICATIONS; REMOTE SENSING IMAGES; SEGMENTATION ALGORITHMS; SEGMENTATION RESULTS;

GENETIC ALGORITHMS;

EID: 85018717000     PISSN: 18632246     EISSN: 18632351     Source Type: Book Series    
DOI: 10.1007/978-3-540-77058-9_37     Document Type: Article

References (16)

1. Baatz M, Schäpe A (2000) Multiresolution Segmentation-an optimization approach for high quality multi-scale image segmentation. In: Strobl J, Blaschke T, Griesebner G (eds) Angewandte Geographische Informationsverarbeitung XII. Wichmann-Verlag, Heidelberg, pp 12-23
2. Blaschke T, Strobl J (2001) What is wrong with pixels? Some recent developments interfacing remote sensing and GIS. GIS-Zeitschrift für Geoinformationssysteme 6:12-17
3. Becerra RL, Coello CAC (2005) Use of domain information to improve the performance of an evolutionary algorithm. In: Proceedings of the 2005 workshops on Genetic and Evolutionary Computation, pp 362-365
4. Bhanu B, Ming JC, Lee S (1991) Closed-loop adaptive image segmentation. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR ’91), pp 734-735
5. Bhanu B, Lee S (1994) Genetic learning for adaptive image segmentation. Kluwer Academic Publishers, Boston
6. Bhanu B, Lee S, Das S (1995) Adaptive image segmentation using genetic and hybrid search methods. IEEE Trans Aero Electron Syst 31:1268-1291
7. Crevier D, Lepage R (1997) Knowledge-based image understanding system: A survey. Comput Vis Image Understand 67:161-185
8. Davis L (1990) Handbook of Genetic Algorithms. Van Nostrand Reinhold Company, New York
9. Darwin C (1859) On the origin of species by means of natural selection, or the preservation of favored races in the struggle for life. John Murray, London
10. Definiens (2004) eCognition Professional: User Guide 4, Definiens Imaging, Munich
11. Espindola GM, Câmara G, Reis IA, Bins LS, Monteiro AM (2006) Parameter selection for region growing image segmentation algorithms using spatial autocorrelation. Int J Rem Sens 27:3035-3040
12. Everingham MR, Muller H, Thomas BT (2002) Evaluating image segmentation algorithms using the pareto front. In: Proceedings of the 7th European Conference on Computer Vision (ECCV2002), part IV (LNCS 2353), pp 34-48
13. Matsuyama T (1993) Expert system for image processing, analysis, and recognition: declarative knowledge representation for computer vision. Adv Electron Electron Phys 86:81-171
14. Michalewicz Z (1994) Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, Berlin Heidelberg New York
15. Schneider W, Eckstein W, Steger C (1997) Real-time visualization of interactive parameter changes in image processing systems. In: Grinstein GG, Erbacher RF (eds) Proceedings of the SPIE: Visual Data Exploration and Analysis IV, vol 3017. SPIE, San Jose, pp 286-295
16. Zhang YJ (1996) A survey on evaluation methods for image segmentation. Pattern Recogn, vol 29, 8:1335-1346