The Boru Data Crawler for Object Detection Tasks in Machine Vision

  • Daniel Howard
  • Simon C. Roberts
  • Conor Ryan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2279)


A’ data crawler’ is allowed to meander around an image deciding what it considers to be interesting and laying down flags in areas where its interest has been aroused. These flags can be analysed statistically as if the image was being viewed from afar to achieve object recognition. The guidance program for the crawler, the program which excites it to deposit a flag and how the flags are combined statistically, are driven by an evolutionary process which has as objective the minimisation of misses and false alarms. The crawler is represented by a tree-based Genetic Programming (GP) method with fixed architecture Automatically Defined Functions (ADFs). The crawler was used as a post-processor to the object detection obtained by a Staged GP method, and it managed to appreciably reduce the number of false alarms on a real-world application of vehicle detection in infrared imagery.


False Alarm False Alarm Rate Machine Vision Vehicle Detection Infrared Imagery 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Daniel Howard
    • 1
  • Simon C. Roberts
    • 1
  • Conor Ryan
    • 2
  1. 1.QinetiQ Software Evolution CentreMalvernUK
  2. 2.Department of Computer ScienceUniversity of LimerickIreland

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