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  • Cybernetics, Artificial Intelligence and Robotics  (1)
  • Key words:Document image analysis – Graphics recognition – Line finding – Performance evaluation – Pattern recognition  (1)
  • Map Interpretation  (1)
  • 1
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    Graphics Recognition Methods and Applications : First International Workshop University Park, PA, USA, August 10–11, 1995 Selected Papers (1996)
    Berlin ; Heidelberg : Springer
    Details
    Keywords: Dokument-Bildanalyse - Engineering Drawings - Erkennungsalgorithmen - Graphics Recognition - Ingenieurzeichnungen ; Landkarteninterpretation ; Map Interpretation ; Recognition Algorithms ; algorithms ; cognition ; construction ; knowledge ; learning ; model ; verificat
    Description / Table of Contents: This book contains revised refereed papers selected from the presentations at the First International Workshop on Graphics Recognition, held in University Park, PA, USA, in August 1995. The 23 full papers included are divided into sections on low-level processing, vectorization and segmentation of scanned graphics documents; symbol and diagram recognition, map processing, interpretation of engineering drawings. Each section contains both survey articles to assess the state of the art, and research papers presenting novel results. One section is devoted to a contest held to determine the best algorithm for detection of dashed lines in drawings. The final chapter summarizes the conclusions and recommendations of the discussions held during the workshop.
    Pages: Online-Ressource (X, 314 pages)
    ISBN: 9783540683872
    URL: https://doi.org/10.1007/3-540-61226-2
    Language: English
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    E-BOOK
  • 2
    Electronic Resource
    Electronic Resource
    Efficient extraction of primitives from line drawings composed of horizontal and vertical lines (1997)
    Springer
    Machine vision and applications 10 (1997), S. 214-221 
    Details
    ISSN: 1432-1769
    Keywords: Key words:Document image analysis – Graphics recognition – Line finding – Performance evaluation – Pattern recognition
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract. The performance of the algorithms for the extraction of primitives for the interpretation of line drawings is usually affected by the degradation of the information contained in the document due to factors such as low print contrast, defocusing, skew, etc. In this paper, we are proposing two algorithms for the extraction of primitives with good performance under degradation. The application of the algorithms is restricted to line drawings composed of horizontal and vertical lines. The performance of the algorithms has been evaluated by using a protocol described in the literature.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s001380050073
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    Paper (German National Licenses)
    Fulltext
  • 3
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    Wire Detection Algorithms for Navigation (2002)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. Wires present a serious hazard to rotorcrafts. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. Two approaches were explored for this purpose. The first approach involved a technique for sub-pixel edge detection and subsequent post processing, in order to reduce the false alarms. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. The performance of the algorithm was evaluated both, at the pixel and the wire levels. It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter. The second approach involved the use of an example-based learning scheme namely, Support Vector Machines. The purpose of this approach was to explore the feasibility of an example-based learning based approach for the task of detecting wires from their images. Support Vector Machines (SVMs) have emerged as a promising pattern classification tool and have been used in various applications. It was found that this approach is not suitable for very thin wires and of course, not suitable at all for sub-pixel thick wires. High dimensionality of the data as such does not present a major problem for SVMs. However it is desirable to have a large number of training examples especially for high dimensional data. The main difficulty in using SVMs (or any other example-based learning method) is the need for a very good set of positive and negative examples since the performance depends on the quality of the training set.
    Keywords: Cybernetics, Artificial Intelligence and Robotics
    Format: application/pdf
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