- 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, http://dblp.uni-trier.de",
-
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.",
