Accurate Centerline Detection and Line Width Estimation of Thick Lines Using the Radon Transform

Zhang, Qiaoping; Couloigner, Isabelle

doi:10.1109/tip.2006.887731

Cited by 121 publications

(65 citation statements)

References 9 publications

(16 reference statements)

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“…These measurements aimed at comparing different bundle thicknesses to contractile dynamics. Bundle widths were evaluated via a Radon transform along the bundle backbone [19]. Some of these measurements were discarded since these evaluations showed a dependency on input parameters.…”

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confidence: 99%

Transition from a Linear to a Harmonic Potential in Collective Dynamics of a Multifilament Actin Bundle

et al. 2016

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Modeling approaches of suspended, rod-like particles and recent experimental data have shown that depletion forces display different signatures depending on the orientation of these particles. It has been shown that axial attraction of two rods yields contractile forces of 0.1 pN that are independent of the relative axial shift of the two rods. Here, we measured depletion-caused interactions of actin bundles extending the phase space of single pairs of rods to a multi-particle system. In contrast to a filament pair, we found forces up to 3 pN. Upon bundle relaxation forces decayed exponentially with a mean decay time of 3.4 s. These different dynamics are explained within the frame of a mathematical model by taking pairwise interactions to a multi-filament scale. The macromolecular content employed for our experiments is well below the crowding of cells. Thus, we propose that arising forces can contribute to biological force generation without the need to convert chemical energy into mechanical work.

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mentioning

confidence: 99%

Transition from a Linear to a Harmonic Potential in Collective Dynamics of a Multifilament Actin Bundle

et al. 2016

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“…Generally speaking, Radon transform decomposes a function in terms of its integral projections [9,17,18,[23][24][25]27]. Let be the ROI of palmprint which contains the principal lines.…”

Section: Radon Transformmentioning

confidence: 99%

A Robust Technique to Characterize the Palmprint using Radon transform and Delaunay triangulation

Bouchemha¹,

Naït‐Ali²,

Doghmane³

2010

IJCA

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For the purpose of biometric applications, we explore in this paper a new robust approach to characterizing palmprint features. Instead of processing the acquired image in the spatial domain, the proposed technique extracts palmprint features using Radon transform and a geometric Delaunay triangulation jointly. In such a process, Radon transform enables the extraction of directional characteristics from the palm of the hand. Afterwards, the most significant information is structured using Delaunay triangulation, thus providing a specific palmprint signature. In order to compare the uniqueness as well as the stability of the palmprint signature, Hausdorff distance has been used as a criterion of similarity. As will be shown in this paper, the palmprint signature is very robust even when considering a low Signal-to-Noise Ratio (SNR). Promising results are obtained from a local database containing 200 palmprint images. This technique is mainly appropriate for authentication applications.

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“…Most previous methods initialize the algorithms by pixel based or line based detection/classification/segmentation (Hinz 2003;Zhang 2007;Close, 2004). Segment primitives and connection hypothesis are needed for most pixel based or object based road extraction.…”

Section: Introductionmentioning

confidence: 99%

Road Network Extraction From DSM by Mathematical Morphology and Reasoning

Zhu³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The objective of this research is the automatic extraction of the road network in a scene of the urban area from a high resolution digital surface model (DSM). Automatic road extraction and modeling from remote sensed data has been studied for more than one decade. The methods vary greatly due to the differences of data types, regions, resolutions et al. An advanced automatic road network extraction scheme is proposed to address the issues of tedium steps on segmentation, recognition and grouping. It is on the basis of a geometric road model which describes a multiple-level structure. The 0-dimension element is intersection. The 1-dimension elements are central line and side. The 2-dimension element is plane, which is generated from the 1-dimension elements. The key feature of the presented approach is the cross validation for the three road elements which goes through the entire procedure of their extraction. The advantage of our model and method is that linear elements of the road can be derived directly, without any complex, non-robust connection hypothesis. An example of Japanese scene is presented to display the procedure and the performance of the approach.

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Accurate Centerline Detection and Line Width Estimation of Thick Lines Using the Radon Transform

Cited by 121 publications

References 9 publications

Transition from a Linear to a Harmonic Potential in Collective Dynamics of a Multifilament Actin Bundle

Transition from a Linear to a Harmonic Potential in Collective Dynamics of a Multifilament Actin Bundle

A Robust Technique to Characterize the Palmprint using Radon transform and Delaunay triangulation

Road Network Extraction From DSM by Mathematical Morphology and Reasoning

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