Topographic cellular active contour techniques: theory, implementations and comparisons

Hillier, Dániel; Binzberger, Viktor; Vilariño, D.L.; Rekeczky, Csaba

doi:10.1002/cta.337

Cited by 13 publications

(6 citation statements)

References 14 publications

(16 reference statements)

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“…Wave-based distance calculation was applied for evaluating errors in different active contour techniques Reference [27]. This technique can also be used for the assessment of contour estimation in the tracking of heart movement in echocardiography applications.…”

Section: Conclusion and Possible Applicationsmentioning

confidence: 99%

Object comparison using PDE‐based wave metric on cellular neural networks

Szatmári

2006

Circuit Theory & Apps

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SUMMARYThe paper investigates PDE-based dynamic phenomena for comparing objects and introduces a spatiotemporal non-linear wave metric. This metric is capable of comparing both binary and grey-scale object pairs in a parallel way. Spatio-temporal waves are initialized and controlled to explore the quantitative properties of objects. In addition to spatial data, even 'hidden', time-related information is also extracted and used for evaluating differences and similarities. The detailed analysis of the proposed metric shows that this wave-based approach can outperform well-known metrics such as Hausdorff and Hamming metrics in selectivity and sensitivity. The approach in question can be efficiently implemented on massively parallel architectures, e.g. on Cellular Neural/Non-linear Networks (CNN), providing solutions either for real time applications.

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Section: Conclusion and Possible Applicationsmentioning

confidence: 99%

Object comparison using PDE‐based wave metric on cellular neural networks

Szatmári

2006

Circuit Theory & Apps

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“…for t 0, where z = x − satisfies Equation (10). Note that V is absolutely continuous on any compact interval in [0, +∞).…”

Section: Proof Of Theoremmentioning

confidence: 99%

On global exponential stability of standard and full‐range CNNs

Marco

Forti

Grazzini

et al. 2007

Circuit Theory & Apps

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SUMMARYThis paper compares the dynamical behaviour of the standard (S) cellular neural networks (CNNs) and the full-range (FR) CNNs, when the two CNN models are characterized by the same set of parameters (interconnections and inputs). The FR-CNNs are assumed to be characterized by ideal hard-limiter nonlinearities with two vertical segments in the i-v characteristic. The main result is that some basic conditions ensuring global exponential stability (GES) of the unique equilibrium point of S-CNNs, with or without delay, continue to ensure the same property for FR-CNNs for the same set of parameters. The significance of this result is discussed with respect to the results in a paper by Corinto and Gilli addressing the similarity of the qualitative behaviour of S-CNNs and FR-CNNs. FR-CNNs are analysed in this paper from a rigorous mathematical viewpoint by means of theoretical tools from set-valued analysis and differential inclusions. In particular, GES is investigated via an extended Lyapunov approach that is applicable to the differential inclusion describing the dynamics of FR-CNNs.

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“…It should be noted, that in theory a CNN-type array processor could handle hole-filling in a single operation, using the 'hole_fill' template. However, the difficulty in implementing an 'ideal' CNN processor in silicon [7,8] leads to the situation that hole-filling still has to be implemented iteratively, even on the most recent CNN chips [6]. Simple, robust solutions for hole-filling exist, based on asynchronous cellular logic [9].…”

Section: Proposed Algorithmmentioning

confidence: 99%

“…The iterative computation of PLS allows an efficient control of the contour evolution. However, as a consequence of the explicit representation of the active contours, the algorithm complexity of PLS is clearly higher than the active wave based approaches [6].…”

Section: Introductionmentioning

confidence: 99%

A Cellular Active Contours Algorithm Based on Region Evolution

Dudek

Vilariño

2006

2006 10th International Workshop on Cellular Neural Networks and Their Applications

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Abstract-This paper introduces a new algorithm for implementing cellular active contour technique based on pixellevel snakes (PLS). The main motivation is the optimization of the computational performance, especially when PLS are implemented on pixel-parallel single instruction multiple data (SIMD) processor arrays. The algorithm is based on the evolution of an active region. This allows the implementation of the entire algorithm using very simple local rules. Additionally, nested contours and propagation into narrow cavities are supported. The algorithm and experimental results from realtime implementation on vision chips are presented.

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Topographic cellular active contour techniques: theory, implementations and comparisons

Cited by 13 publications

References 14 publications

Object comparison using PDE‐based wave metric on cellular neural networks

Object comparison using PDE‐based wave metric on cellular neural networks

On global exponential stability of standard and full‐range CNNs

A Cellular Active Contours Algorithm Based on Region Evolution

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