MURAL - Maynooth University Research Archive Library



    Topographic Object Recognition Through Shape


    Keyes, Laura and Winstanley, Adam C. (2001) Topographic Object Recognition Through Shape. Technical Report. Technical Report NUIM/SS/--/2001/06, Computer Science, NUIM.. (Unpublished)

    [img] Download (358kB)


    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...



    Add this article to your Mendeley library


    Abstract

    Automatic structuring (feature coding and object recognition) of topographic data, such as that derived from air survey or raster scanning large-scale paper maps, requires the classification of objects such as buildings, roads, rivers, fields and railways. The recognition of objects in computer vision is largely based on the matching of descriptions of shapes. Fourier descriptors, moment invariants, boundary chain coding and scalar descriptors are methods that have been widely used and have been developed to describe shape irrespective of position, orientation and scale. The applicability of the above four methods to topographic shapes is described and their usefulness evaluated. All methods derive descriptors consisting of a small number of real values from the object's polygonal boundary. Two large corpora representing data sets from Ordnance Survey maps of Purbeck and Plymouth were available. The effectiveness of each description technique was evaluated by using one corpus as a training-set to derive distributions for the values for supervised learning. This was then used to reclassify the objects in both data sets using each individual descriptor to evaluate their effectiveness. No individual descriptor or method produced consistent correct classification. Various models for the fusion of the classification results from individual descriptors were implemented. These were used to experiment with different combinations of descriptors in order to improve results. Overall results show that Moment Invariants fused with the minfusion rule gave the best performance with the two data sets. Much further work remains to be done as enumerated in the concluding section.

    Item Type: Monograph (Technical Report)
    Keywords: Shape description; classification; fourier descriptors; moment invariants; fusion;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Social Sciences > Geography
    Item ID: 9
    Depositing User: Dr. Adam Winstanley
    Date Deposited: 21 May 2002
    Publisher: Technical Report NUIM/SS/--/2001/06, Computer Science, NUIM.
    Refereed: No
    URI:
      Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

      Repository Staff Only(login required)

      View Item Item control page

      Downloads

      Downloads per month over past year

      Origin of downloads