Best cited publications of N. Petkov

Contours, edges, nonclassical receptive field inhibition, surround suppression, areas V1 and V2 of visual cortex, Gabor filters, simple and complex cells

• G. Papari and N. Petkov: Edge and line oriented contour detection: State of the art. Image and Vision Computing, 29 (2-3), Feb. 2011, 79-103.
  [bib], [pdf © Elsevier], [doi: 10.1016/j.imavis.2010.08.009].
• G. Papari, P. Campisi, N. Petkov and A. Neri: A biologically motivated multiresolution approach to contour detection, EURASIP Journal on Advances in Signal Processing, Vol. 2007, Article ID 71828, 28 pages, 2007.
  [bib], [pdf © 2007 G. Papari, P. Campisi, N. Petkov and A. Neri], [DOI 10.1155/2007/71828], [supplementary illustrations]
• C. Grigorescu, N. Petkov and M. A. Westenberg: Contour and boundary detection improved by surround suppression of texture edges, Image and Vision Computing, 22 (8), 2004, 609-622.
  [bib], [pdf , html, © Elsevier], [DOI 10.1016/j.imavis.2003.12.004].
• C. Grigorescu, N. Petkov and M. A. Westenberg: Contour detection based on nonclassical receptive field inhibition, IEEE Trans. on Image Processing, 12 (7), 2003, 729-739.
  [bib], [pdf © IEEE], [demo and database].
• N. Petkov and M. A. Westenberg: Suppression of contour perception by band-limited noise and its relation to non-classical receptive field inhibition, Biological Cybernetics, 88, 2003, 236-246.
  [bib], [pdf © Springer], [DOI 10.1007/s00422-002-0378-2], [demo],

Shape

• A. Ghosh and N. Petkov: Robustness of shape descriptors to incomplete contour representations, IEEE Trans. on Pattern Analysis and Machine Intelligence, 27 (11), 2005, 1793-1804.
  [bib], [pdf © IEEE], [ICR test database].
• C. Grigorescu and N. Petkov: Distance sets for shape filters and shape recognition, IEEE Trans. on Image Processing, 12 (10), 2003, 1274-1286.
  [bib], [pdf © IEEE]

Texture, areas V1 and V2 of visual cortex, Gabor filters, simple and complex cells, grating cells

• S.E. Grigorescu, N. Petkov and P. Kruizinga: Comparison of texture features based on Gabor filters, IEEE Trans. on Image Processing, 11 (10), 2002, 1160-1167.
  [bib], [pdf © IEEE]
• P. Kruizinga and N. Petkov: Non-linear operator for oriented texture, IEEE Trans. on Image Processing, 8 (10), 1999, 1395-1407.
  [bib], [pdf © IEEE]
• P. Kruizinga, N. Petkov and S.E. Grigorescu: Comparison of texture features based on Gabor filters. Proc. Int. Conf. on Image Analysis and Processing (ICIAP'99), September 27-29, 1999, Venice, Italy (IEEE Computer Society: Los Alamitos, California, 1999) pp.142-147.
• P. Kruizinga and N. Petkov: Grating cell operator features for oriented texture. Proc. Int. Conf. on Pattern Recognition, 1998, IEEE, Brisbane, Australia, Aug. 16-20, pp. 1010-1014.
  [pdf © IEEE]
• N. Petkov and P. Kruizinga: Computational models of visual neurons specialised in the detection of periodic and aperiodic oriented visual stimuli: bar and grating cells, Biological Cybernetics, 76 (2), 1997, 83-96.
  [bib], [pdf © Springer]
• N. Petkov: Biologically motivated computationally intensive approaches to image pattern recognition, Future Generation Computer Systems, 11 (4-5), 1995, 451-465.
  [bib], [pdf , html © Elsevier], [DOI 10.1016/0167-739X(95)00015-K].
• N. Petkov, P. Kruizinga and T. Lourens: Biologically Motivated Approach to Face Recognition. Proc. Int. Workshop on Artificial Neural Networks, IWANN '93, June 9-11, 1993, Sitges (Barcelona), Spain, Lecture Notes in Computer Science, Vol.686, (Berlin: Springer, 1993) pp.68-77.

Parallel Computing

• N. Petkov: Systolic Parallel Processing (Amsterdam: North-Holland, Elsevier Sci. Publ., 1993; ISBN 0-444-88769-5) xx + 712 pages, 300 figures.

Last changed: 2011-12-30.