Genetic Programming for Algae Detection in River Images

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Lensen:2015:CEC,

• author = "Andrew Lensen and Harith Al-Sahaf and Mengjie Zhang and Brijesh Verma",
• title = "Genetic Programming for Algae Detection in River Images",
• booktitle = "Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC 2015)",
• year = "2015",
• editor = "Yadahiko Murata",
• pages = "2468--2475",
• address = "Sendai, Japan",
• month = "25-28 " # may,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/CEC.2015.7257191",
• abstract = "Genetic Programming (GP) has been applied to a wide range of image analysis tasks including many real-world segmentation problems. This paper introduces a new biological application of detecting Phormidium algae in rivers of New Zealand using raw images captured from the air. In this paper, we propose a GP method to the task of algae detection. The proposed method synthesises a set of image operators and adopts a simple thresholding approach to segmenting an image into algae and non-algae regions. Furthermore, the introduced method operates directly on raw pixel values with no human assistance required. The method is tested across seven different images from different rivers. The results show good success on detecting areas of algae much more efficiently than traditional manual techniques. Furthermore, the result achieved by the proposed method is comparable to the hand-crafted ground truth with a F-measure fitness value of 0.64 (where 0 is best, 1 is worst) on average on the test set. Issues such as illumination, reflection and waves are discussed.",
• notes = "1645 hrs 15398 CEC2015",

}

Genetic Programming entries for Andrew Lensen Harith Al-Sahaf Mengjie Zhang Brijesh Verma

Citations