Design of efficient line segment detectors for cereal grain inspection

Authors:
E. R. Davies;M. Bateman;D. R. Mason;J. Chambers;C. Ridgway
Affiliations:
Machine Vision Group, Department of Physics, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK;Machine Vision Group, Department of Physics, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK;Machine Vision Group, Department of Physics, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK;Central Science Laboratory, Sand Hutton York, YO41 1LZ, UK;Central Science Laboratory, Sand Hutton York, YO41 1LZ, UK
Venue:
Pattern Recognition Letters
Year:
2003

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Abstract

This paper shows how line segment detection can be achieved with a minimum of computation if two masks embodying a vectorial design strategy are employed. To achieve the greatest combination of accuracy and speed, a two-stage procedure was used with the vectorial operator backed up by a template matching technique. Experimental tests verified the effectiveness of this type of line segment detector for locating insects in cereal grain images: in a set of 60 images containing 150 insects, there were no false positives and the only false negative arose from two insects which were in contact. The approach should be useful in a good many other areas ranging from industrial inspection to document processing and remote sensing--and indeed, in the many applications where line segments have to be located or thin lines have to be tracked.