Image Processing Reference
In-Depth Information
57. Bilotta, E., Lafusa, A., Pantano, P.: Searching for complex CA rules with GAs. Com-
plexity 8(3), 56-67 (2003)
58. Birajdar, G.K., Mankar, V.H.: Digital image forgery detection using passive techniques:
A survey. Digital Investigation 10(3), 226-245 (2013)
59. Blum, H.: An associative machine for dealing with the visual field and some of its
biological implications. In: Bernard, E.E., Kare, M.R. (eds.) Biological Prototypes and
Synthetic Systems, vol. 1, pp. 244-260. Plenum Press, New York (1962), Proceedings
of the 2nd Annual Bionics Symposium, held at Cornell University (1961)
60. Bodart, M., De Herde, A.: Global energy savings in offices buildings by the use of
daylighting. Energy and Buildings 34(5), 421-429 (2002)
61. Boden, M.A., Edmonds, E.A.: What is generative art? Digital Creativity 20(1-2), 21-46
(2009)
62. Borsani, C., Cattaneo, G., Mattei, V., Jocher, U., Zampini, B.: 2d and 3d lattice gas
techniques for fluid-dynamics simulations. In: Bandini, S., Serra, R., Liverani, F. (eds.)
Cellular Automata: Research Towards Industry, pp. 67-79. Springer, London (1998)
63. Botha, L., Van Zijl, L., Hoffmann, M.: Realtime LEGO brick image retrieval with cel-
lular automata. Journal of Universal Computer Science 15(14), 2765-2785 (2009)
64. Bovik, A.C.: The essential guide to image processing. Academic Press (2009)
65. Boyce, P.: Why Daylight? In: Proceedings of Daylight 1998, International Confer-
ence on Daylighting Technologies for Energy Efficiency in Buildings, Ottawa, Ontario,
Canada, pp. 359-365 (1998)
66. Boyce, P., Hunter, C., Howlett, O.: The benefits of daylight through windows: Report.
Tech. rep., Rensselaer Polytechnic Institute, Troy, New York (2003)
67. Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max-flow algo-
rithms for energy minimization in vision. IEEE Transactions on Pattern Analysis and
Machine Intelligence 26(9) (2004)
68. Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph
cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(11), 1222-
1239 (2001)
69. Boykov, Y.Y., Jolly, M.P.: Interactive graph cuts for optimal boundary and region seg-
mentation of objects in ND images. In: Proceedings of the Eighth IEEE International
Conference on Computer Vision (ICCV 2001), vol. 1, pp. 105-112. IEEE (2001)
70. Bravo-Solorio, S., Nandi, A.K.: Exposing duplicated regions affected by reflection, ro-
tation and scaling. In: International Conference on Acoustics, Speech and Signal Pro-
cessing, pp. 1880-1883 (2011)
71. Brown, P.: Emergent behaviours towards computational aesthetics. Artlink 16(2-3)
(1996)
72. Bruckstein, A.M., Holt, R.J., Netravali, A.N.: Holographic representation of images.
IEEE Trans. Image Processing 7, 1583-1597 (1998)
73. Bubna, M., Roy, S., Shenoy, N., Mazumdar, S.: A layout-aware physical design method
for constructing feasible QCA circuits. In: Proceedings of the ACM Great Lakes Sym-
posium on VLSI, GLSVLSI, pp. 243-248 (2008)
74. Burraston, D.: Generative music and cellular automata: An introduction to the online
bibliography. Leonardo 45(2), 165-165 (2012)
75. Burraston, D., Edmonds, E.: Cellular automata in generative electronic music and sonic
art: a historical and technical review. Digital Creativity 16(3), 165-185 (2005)
76. Burt, P.J., Adelson, E.H.: The Laplacian pyramid as a compact image code. IEEE Trans.
on Communications COM 31(4), 532-540 (1983)
77. Burt, W.A.: Cellular automata as spectra: Beyond sonification into composition. In:
Riddell, A., Thorogood, A. (eds.) Proceedings of the Australasian Computer Music
Conference, Canberra, Australia, pp. 27-33 (2007)
Search WWH ::




Custom Search