Program Size and Pixel Statistics in Genetic Programming for Object Detection

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{zhang2:evows04,

• author = "Mengjie Zhang and Urvesh Bhowan",
• title = "Program Size and Pixel Statistics in Genetic Programming for Object Detection",
• booktitle = "Applications of Evolutionary Computing, EvoWorkshops2004: {EvoBIO}, {EvoCOMNET}, {EvoHOT}, {EvoIASP}, {EvoMUSART}, {EvoSTOC}",
• year = "2004",
• month = "5-7 " # apr,
• editor = "Guenther R. Raidl and Stefano Cagnoni and Jurgen Branke and David W. Corne and Rolf Drechsler and Yaochu Jin and Colin R. Johnson and Penousal Machado and Elena Marchiori and Franz Rothlauf and George D. Smith and Giovanni Squillero",
• series = "LNCS",
• volume = "3005",
• address = "Coimbra, Portugal",
• publisher = "Springer Verlag",
• publisher_address = "Berlin",
• pages = "379--388",
• keywords = "genetic algorithms, genetic programming, evolutionary computation",
• ISBN = "3-540-21378-3",
• DOI = "doi:10.1007/978-3-540-24653-4_39",
• abstract = "This paper describes an approach to the use of genetic programming for object detection problems. In this approach, local region pixel statistics are used to form three terminal sets. The function set is constructed by the four standard arithmetic operators and a conditional operator. A multi-objective fitness function is constructed based on detection rate, false alarm rate, false alarm area and program size. This approach is applied to three object detection problems of increasing difficulty. The results suggest that the concentric circular pixel statistics are more effective than the square features for the coin detection problems. The fitness function with program size is more effective and more efficient for these object detection problems and the evolved genetic programs using this fitness function are much shorter and easier to interpret.",
• notes = "EvoWorkshops2004",

}

Genetic Programming entries for Mengjie Zhang Urvesh Bhowan

Citations