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Computer-vision-based tree trunk recognition

Matic Švab (2014) Computer-vision-based tree trunk recognition. EngD thesis.

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    This thesis presents a process of a tree recognition by means of the computer vision, which analyses the tree bark. The procedure extracts LBP features from individual pictures of bark, which are used for training and testing by SVM. Since freely accessible collection of tree bark pictures does not exist, it was necessary to create a larger annotated collection which is also the first database publicly available. In recognition there is also a problem with scale or picture size, because different devices take pictures of different sizes, in different width/height proportions and mostly people do not take photographs from the same distance. The thesis also proposes a procedure that by means of the features gained by DoG detector, automatically determines the picture scale, by means of which the input picture is always rescaled in the reference size before the calculation of LBP. In the final experiment the 84.62 % accuracy was achieved on the collection of 12 trees.

    Item Type: Thesis (EngD thesis)
    Keywords: local binary patterns, support vector machine, tree classification, automatic scale determination
    Number of Pages: 46
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Matej Kristan4053Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1536123331)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 2742
    Date Deposited: 19 Sep 2014 17:52
    Last Modified: 18 Dec 2014 14:10
    URI: http://eprints.fri.uni-lj.si/id/eprint/2742

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