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  • 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
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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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    NASA TECHNICAL REPORTS
  • 3
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    Algorithms for detection of objects in image sequences captured from an airborne imaging system (1995)
    In:  CASI
    Details
    Publication Date: 2019-07-13
    Description: This research was initiated as a part of the effort at the NASA Ames Research Center to design a computer vision based system that can enhance the safety of navigation by aiding the pilots in detecting various obstacles on the runway during critical section of the flight such as a landing maneuver. The primary goal is the development of algorithms for detection of moving objects from a sequence of images obtained from an on-board video camera. Image regions corresponding to the independently moving objects are segmented from the background by applying constraint filtering on the optical flow computed from the initial few frames of the sequence. These detected regions are tracked over subsequent frames using a model based tracking algorithm. Position and velocity of the moving objects in the world coordinate is estimated using an extended Kalman filter. The algorithms are tested using the NASA line image sequence with six static trucks and a simulated moving truck and experimental results are described. Various limitations of the currently implemented version of the above algorithm are identified and possible solutions to build a practical working system are investigated.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: NASA-CR-199579 , NAS 1.26:199579 , CSE-95-026
    Format: application/pdf
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    NASA TECHNICAL REPORTS
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