Genetic programming based image segmentation with applications to biomedical object detection

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Tarundeep Singh and Nawwaf N. Kharma and 
                 Mohmmad Daoud and Rabab Ward",
  title =        "Genetic programming based image segmentation with
                 applications to biomedical object detection",
  booktitle =    "GECCO '09: Proceedings of the 11th Annual conference
                 on Genetic and evolutionary computation",
  year =         "2009",
  editor =       "Guenther Raidl and Franz Rothlauf and 
                 Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and 
                 Mauro Birattari and Clare Bates Congdon and 
                 Martin Middendorf and Christian Blum and Carlos Cotta and 
                 Peter Bosman and Joern Grahl and Joshua Knowles and 
                 David Corne and Hans-Georg Beyer and Ken Stanley and 
                 Julian F. Miller and Jano {van Hemert} and 
                 Tom Lenaerts and Marc Ebner and Jaume Bacardit and 
                 Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and 
                 Thomas Jansen and Riccardo Poli and Enrique Alba",
  pages =        "1123--1130",
  address =      "Montreal",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "8-12 " # jul,
  organisation = "SigEvo",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-60558-325-9",
  bibsource =    "DBLP,",
  DOI =          "doi:10.1145/1569901.1570052",
  abstract =     "Image segmentation is an essential process in many
                 image analysis applications and is mainly used for
                 automatic object recognition purposes. In this paper,
                 we define a new genetic programming based image
                 segmentation algorithm (GPIS). It uses a primitive
                 image-operator based approach to produce linear
                 sequences of MATLAB code for image segmentation. We
                 describe the evolutionary architecture of the approach
                 and present results obtained after testing the
                 algorithm on a biomedical image database for cell
                 segmentation. We also compare our results with another
                 EC-based image segmentation tool called GENIE Pro. We
                 found the results obtained using GPIS were more
                 accurate as compared to GENIE Pro. In addition, our
                 approach is simpler to apply and evolved programs are
                 available to anyone with access to MATLAB",
  notes =        "GECCO-2009 A joint meeting of the eighteenth
                 international conference on genetic algorithms
                 (ICGA-2009) and the fourteenth annual genetic
                 programming conference (GP-2009).

                 ACM Order Number 910092.",

Genetic Programming entries for Tarundeep Singh Nawwaf Kharma Mohmmad Daoud Rabab K Ward