Rotation Invariant Detection of Moving and Standing Objects Using Analogic Cellular Neural Network Algorithms Based on Ring-Codes
Summary :
Cellular Neural Networks (CNNs) are nonlinear dynamic array processors with mainly local interconnections. In most of the applications, the local interconnection pattern, called cloning template, is translation invariant. In this paper, an optimal ring-coding method for rotation invariant description of given set of objects, is introduced. The design methodology of the templates based on the ring-codes and the synthesis of CNN analogic algorithms to detect standing and moving objects in a rotationally invariant way, discussed in detail. It is shown that the algorithms can be implemented using the CNN Universal Machine, the recently invented analogic visual microprocessor. The estimated time performance and the parallel detecting capability is emphasized, the limitations are also thoroughly investigated.
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- IEICE TRANSACTIONS on Fundamentals Vol.E78-A No.10 pp.1316-1330
- Publication Date
- 1995/10/25
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- Type of Manuscript
- Special Section PAPER (Special Section on Nonlinear Theory and Its Applications)
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Csaba REKECZKY, Akio USHIDA, Tamás ROSKA, "Rotation Invariant Detection of Moving and Standing Objects Using Analogic Cellular Neural Network Algorithms Based on Ring-Codes" in IEICE TRANSACTIONS on Fundamentals,
vol. E78-A, no. 10, pp. 1316-1330, October 1995, doi: .
Abstract: Cellular Neural Networks (CNNs) are nonlinear dynamic array processors with mainly local interconnections. In most of the applications, the local interconnection pattern, called cloning template, is translation invariant. In this paper, an optimal ring-coding method for rotation invariant description of given set of objects, is introduced. The design methodology of the templates based on the ring-codes and the synthesis of CNN analogic algorithms to detect standing and moving objects in a rotationally invariant way, discussed in detail. It is shown that the algorithms can be implemented using the CNN Universal Machine, the recently invented analogic visual microprocessor. The estimated time performance and the parallel detecting capability is emphasized, the limitations are also thoroughly investigated.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e78-a_10_1316/_p
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@ARTICLE{e78-a_10_1316,
author={Csaba REKECZKY, Akio USHIDA, Tamás ROSKA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Rotation Invariant Detection of Moving and Standing Objects Using Analogic Cellular Neural Network Algorithms Based on Ring-Codes},
year={1995},
volume={E78-A},
number={10},
pages={1316-1330},
abstract={Cellular Neural Networks (CNNs) are nonlinear dynamic array processors with mainly local interconnections. In most of the applications, the local interconnection pattern, called cloning template, is translation invariant. In this paper, an optimal ring-coding method for rotation invariant description of given set of objects, is introduced. The design methodology of the templates based on the ring-codes and the synthesis of CNN analogic algorithms to detect standing and moving objects in a rotationally invariant way, discussed in detail. It is shown that the algorithms can be implemented using the CNN Universal Machine, the recently invented analogic visual microprocessor. The estimated time performance and the parallel detecting capability is emphasized, the limitations are also thoroughly investigated.},
keywords={},
doi={},
ISSN={},
month={October},}
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TY - JOUR
TI - Rotation Invariant Detection of Moving and Standing Objects Using Analogic Cellular Neural Network Algorithms Based on Ring-Codes
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1316
EP - 1330
AU - Csaba REKECZKY
AU - Akio USHIDA
AU - Tamás ROSKA
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E78-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 1995
AB - Cellular Neural Networks (CNNs) are nonlinear dynamic array processors with mainly local interconnections. In most of the applications, the local interconnection pattern, called cloning template, is translation invariant. In this paper, an optimal ring-coding method for rotation invariant description of given set of objects, is introduced. The design methodology of the templates based on the ring-codes and the synthesis of CNN analogic algorithms to detect standing and moving objects in a rotationally invariant way, discussed in detail. It is shown that the algorithms can be implemented using the CNN Universal Machine, the recently invented analogic visual microprocessor. The estimated time performance and the parallel detecting capability is emphasized, the limitations are also thoroughly investigated.
ER -
English
