BazEkon - Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie

BazEkon home page

Meny główne

Autor
Bieniecki Wojciech (Lodz University of Technology, Poland), Stoliński Sebastian (Lodz University of Technology, Poland), Stasiak-Bieniecka Magdalena (Lodz University of Technology, Poland)
Tytuł
Computer Aided Assessment of Linear and Quadratic Function Graphs Using Least-squares Fitting
Źródło
Annals of Computer Science and Information Systems, 2014, vol. 2, s. 651 - 658, rys., tab., bibliogr. 18 poz.
Słowa kluczowe
Przetwarzanie obrazu, Algorytmy, Grafy
Image processing, Algorithms, Graphs
Uwagi
summ.
Abstrakt
In this paper an image processing algorithm for automatic evaluation of scanned examination sheets is described. The discussed image contains selected function graphs sketched on a prepared sheets. This type of task is characteristic of final high school exams of natural sciences. Our challenge was to develop an evaluation algorithm, which works with a precision comparable to the teacher. If the image contains the correct solution, the algorithm should husk it from a set of random lines, deletions, amendments, drafts, bearing in mind, that lines were drawn by hand. In addition, the algorithm should calculate scores for partially correct solutions. An essential part of our proposal, which is image segmentation and identification, is based on least-squares fitting combined with 1-NN classification. The proposed solution is flexible and can be extended to other types of tasks such as drawing geometrical figures.(original abstract)
Pełny tekst
Pokaż
Bibliografia
Pokaż
  1. Ahn S. J. and Rauh W. and Warnecke H. -J.: Leastsquares orthogonal distances fitting of circle, sphere, ellipse, hyperbola, and parabola. Pattern Recognition 34(12), 2283 - 2303 (2001). DOI http://dx.doi.org/10.1016/S0031-3203(00)00152-7. URL http://www.sciencedirect.com/science/article/pii/S0031320300001527
  2. Araokar S.: Visual character recognition using artificial neural networks. CoRR abs/cs/0505016 (2005)
  3. Bieniecki W. and Stańdo J. and Stoliński S.: Automatic evaluation of examination tasks in the form of function plot. pp., 140-143. Polytechnic National University (2010)
  4. Croft A. C. and Danson M. and Dawson B. R. and Ward J. P.: Experiences of using computer assisted assessment in engineering mathematics. Computers and Education 37(1), 53-66 (2001). DOI 10.1016/S0360-1315(01)00034-3
  5. Fowles D., Adams C.: How does assessment differ when e-marking replaces paper-based marking? 31st International Association for Educational Assessment Conference, Abuja, Nigeria, 4-9 September 2005 (2005)
  6. Gander W. and Golub G. and Strebel R.: Least-squares fitting of circles and ellipses. BIT Numerical Mathematics 34(4), 558-578 (1994). DOI 10.1007/BF01934268. URL http://dx.doi.org/10.1007/BF01934268
  7. Lewis J. P.: Fast normalized cross-correlation (1995)
  8. Nobuyuki: A Threshold Selection Method from Gray-level Histograms. IEEE Transactions on Systems, Man and Cybernetics 9(1), 62-66 (1979). DOI 10.1109/TSMC.1979.4310076
  9. Prusa D. and Hlavac V.: Ninth International Conference on Document Analysis and Recognition, 2007. ICDAR 2007. pp., 849 -853 (2007). DOI 10.1109/ICDAR.2007.4377035
  10. Sambell K. and Sambell A. and Sexton G.: 19, , pp.179-192. Kogan Page, London (1999)
  11. Sewisy, Adel A.: Graphical techniques for detecting lines with the hough transform. Int. J. Comput. Math. 79(1), 49-64 (2002). DOI 10.1080/00207160211911
  12. Sim G. and Holifield P. and Brown M.: Implementation of computer assisted assessment: lessons from the literature. Research in Learning Technology 12(3) (2004). DOI 10.1080/0968776042000259546
  13. Stoliński S. and Bieniecki W. and Stańdo J.: Automatic detection and evaluation of the spline function plot. Automatyka 14/3/1, 879-896 (2010). DOI http://dx.doi.org/10.7494/automat
  14. Stoliński S. and Bieniecki W.: Application of ocr systems to preprocessing and digitalization of paper documents. pp., 102-111. WULS Press, Warszawa (2011)
  15. Stoliński S. and Bieniecki W.: The algorithms for automatic evaluation of selected examination tasks from the geometry. Automatyka 15/3, 551-560 (2011). DOI http://dx.doi.org/10.7494/automat
  16. Strouthopoulos C. and Papamarkos N.: Text identification for document image analysis using a neural network. Image Vision Comput. 16(12-13), 879-896 (1998). DOI 10.1016/S0262-8856(98)00055-9
  17. Tadeusiewicz R. and Ogiela M. R. and Szczepaniak P. S.: Notes on a linguistic description as the basis for automatic image understanding. Applied Mathematics and Computer Science 19(1), 143-150(2009). DOI 10.1.1.390.8222
  18. Thelwall M.: Computer-based assessment: a versatile educational tool. Computers and Education 34(1), 37-49 (2000). DOI 10.1016/S0360-1315(99)00037-8
Cytowane przez
Pokaż
ISSN
2300-5963
Język
eng
Udostępnij na Facebooku Udostępnij na Twitterze Udostępnij na Google+ Udostępnij na Pinterest Udostępnij na LinkedIn Wyślij znajomemu