Image Processing Reference
In-Depth Information
442. de Saint Pierre, T., Milgram, M.: New and efficient cellular algorithms for image pro-
cessing. CVGIP: Image Understanding 55(3), 261-274 (1992)
443. Sakkal, M.: Art of Arabic Calligraphy (1993),
444. Saponara, S., Fanucci, L., Terreni, P.: Design of a low-power VLSI macrocell for
nonlinear adaptive video noise reduction. Eurasip Journal on Applied Signal Process-
ing 2004(12), 1921-1930 (2004)
445. Sato, S., Kanoh, H.: Evolutionary design of edge detector using rule-changing cellular
automata. In: Nature & Biologically Inspired Computing, pp. 60-65 (2010)
446. Selvapeter, J., Hordijk, W.: Genetically evolved cellular automata for image edge de-
tection. In: Proceedings of the International Conference on Signal, Image Processing
and Pattern Recognition, SIPP 2013 (2013)
447. Selvapeter, P.J., Hordijk, W.: Cellular automata for image noise filtering. In: Proceed-
ings of the World Congress on Nature and Biologically Inspired Computing (NaBIC),
pp. 193-197 (2009)
448. Sen, B., Anand, A.S., Adak, T., Sikdar, B.K.: Thresholding using quantum-dot cellular
automata. In: 2011 International Conference on Innovations in Information Technology,
IIT 2011, pp. 356-360 (2011)
449. Senthilkumar, S., Piah, A.R.M.: An improved fuzzy cellular neural network (IFCNN)
for an edge detection based on parallel RK (5,6) approach. International Journal of
Computational Systems Engineering 1(1), 70-78 (2012)
450. Serra, J.: Image Analysis and Mathematical Morphology. Acad. Press (1993)
451. Serra, R.: Chapter 6 - Daylighting. Renewable and Sustainable Energy Reviews 2(1-2),
115-155 (1998)
452. Shamsabadi, A.S., Ghahfarokhi, B.S., Zamanifar, K., Movahedinia, N.: Applying in-
herent capabilities of quantum-dot cellular automata to design: D flip-flop case study.
Journal of Systems Architecture 55(3), 180-187 (2009)
453. Shanken,
E.A.:
Art
in
the
information
age:
Technology
and
conceptual
art.
Leonardo 35(4), 433-438 (2002)
454. Shanken, E.A.: Cybernetics and art: Cultural convergence in the 1960s. In: Clarke, B.,
Henderson, L.D. (eds.) From Energy to Information, pp. 155-177. Stanford University
Press, Palo Alto (2002)
455. Sharma, P., Lal, N., Diwakar, M.: Text security using 2d cellular automata rules. In:
Proceedings of the Conference on Advances in Communication and Control Systems
2013, Atlantis Press (2013)
456. Shi, H., Ward, R.: Canny edge based image expansion. In: IEEE International Sympo-
sium on Circuits and Systems, pp. 785-788. IEEE, Scottsdale (2002)
457. Shin, M.C., Goldgof, D.B., Bowyer, K.W.: Comparison of edge detector performance
through use in an object recognition task. Computer Vision and Image Understand-
ing 84(1), 160-178 (2001)
458. Shivakumar, B.L., Baboo, S.: Detecting copy-move forgery in digital images: A survey
and analysis of current methods. Global Journal of Computer Science and Technol-
ogy 10(7), 61-65 (2010)
459. Shivakumar, B.L., Baboo, S.: Detection of region duplication forgery in digital images
using surf. International Journal of Computer Science Issues 8(4), 199-205 (2011)
460. Siddiqi, K., Pizer, S.: Medial representations: mathematics, algorithms and applica-
tions. In: Computational Imaging and Vision. Springer (2008)
461. Singer, I.: Abstract convex analysis. John Wiley & Sons Inc., (1997)
462. Sipper, M.: Co-evolving non-uniform cellular automata to perform computations. Phys-
ica D 92, 193-208 (1996)
Search WWH ::
Custom Search