Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking

Miranda, Paulo A. V.; Falcão, Alexandre X.; Spina, Thiago Vallin

doi:10.1109/tip.2012.2188034

Cited by 53 publications

(52 citation statements)

References 35 publications

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“…A thorough evaluation needs to be performed in an extended version of the current paper, including quantification of segmentation accuracy with respect to ground truth segmentations, and evaluation of the sensitivity to several parameters (distribution of initial vertices along the contour, regularization weight, etc. ), as well as comparison with related approaches, such as [17].…”

Section: Resultsmentioning

confidence: 99%

“…Optimality is the main advantage of such approaches, since in most cases, a minimum cost path can be efficiently found as the global solution of the corresponding minimization problem, like Dijkstra's algorithm for shortest paths in directed graphs with no negative cycle. Interactive segmentation methods based on a graph modeling of the image, making them discrete by nature, include the intelligent scissors (or live-wire) [18] and their on-the-fly extension [10], as well as the riverbed approach [17] based on the image foresting transform [11]. As regards continous models, the minimal path method [7] achieved global minimization of the geodesic active contour functional [5], with fixed user-provided endpoints, using the Fast Marching method [20,21].…”

Section: Introductionmentioning

confidence: 99%

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Combination of paths for interactive segmentation

Mille¹,

Bougleux²,

Cohen³

2013

Procedings of the British Machine Vision Conference 2013

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Active contours and minimal paths have been extensively studied theoretical tools for image segmentation. The recent geodesically linked active contour model, which basically consists in a set of vertices connected by paths of minimal cost, blend the benefits of both concepts. This makes up a closed piecewise-smooth curve, over which an edge or region energy functional can be formulated. As an important shortcoming, the geodesically linked active contour model in its initial formulation does not guarantee the curve to be simple, consistent with respect to the purpose of segmentation. In this paper, we propose to extract a relevant contour from a set of possible paths, such that the resulting structure fits the image data and is simple. Toward this goal, we introduce a novel term to favor the simplicity of the generated contour, as well as a local search method to choose the best combination among possible paths.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Combination of paths for interactive segmentation

Mille¹,

Bougleux²,

Cohen³

2013

Procedings of the British Machine Vision Conference 2013

View full text Add to dashboard Cite

show abstract

“…As a summary of the justifications stated in [33], it allows not to favor shortest distance paths and to avoid undesirable shortcuts. Given n initial vertices, n instances of the IFT are run.…”

Section: Overview Of the Riverbed Algorithmmentioning

confidence: 99%

Combination of Piecewise-Geodesic Curves for Interactive Image Segmentation

Mille

Bougleux²,

Cohen³

2015

Curves and Surfaces

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Minimum cost paths have been extensively studied theoretical tools for interactive image segmentation. The existing geodesically linked active contour (GLAC) model, which basically consists of a set of vertices connected by paths of minimal cost, blends the benefits of minimal paths and region-based active contours. This results in a closed piecewise-smooth curve, over which an edge or region energy functional can be formulated. As an important shortcoming, the GLAC in its initial formulation does not guarantee the curve to be simple, consistent with respect to the purpose of segmentation. In this paper, we draw our inspiration from the GLAC and other boundary-based interactive segmentation algorithms, in the sense that we aim to extract a contour given a set of user-provided points, by connecting these points using paths. The key idea is to select a combination among a set of possible paths, such that the resulting structure represents a relevant closed curve. Instead of considering minimal paths only, we switch to a more general formulation, which we refer to as admissible paths. These basically correspond to the roads travelling along the bottom of distinct valleys between given endpoints. We introduce a novel term to

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“…In [25], Spina et al proposed a hybrid interactive segmentation approach, Live markers, by combining the boundary seed-based methods (Live-wire-on-the-fly [26], Riverbed [27]) and region seed-based methods (Image Foresting Transform (IFT) [28], Graph cuts [1]). First, the method tracked object boundary by using user specified boundary seeds; then, the pixels adjacent to the tracked boundary were set as object or background seeds, which initialize the IFT or Graph cuts methods.…”

Section: Introductionmentioning

confidence: 99%

Neutro-Connectedness Cut

Xian

Zhang

Cheng

et al. 2016

IEEE Trans. on Image Process.

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Abstract-Interactive image segmentation is a challenging task and receives increasing attention recently; however, two major drawbacks exist in interactive segmentation approaches. First, the segmentation performance of ROI-based methods is sensitive to the initial ROI: different ROIs may produce results with great difference. Second, most seed-based methods need intense interactions, and are not applicable in many cases.In this work, we generalize the Neutro-Connectedness (NC) to be independent of top-down priors of objects and to model image topology with indeterminacy measurement on image regions, propose a novel method for determining object and background regions, which is applied to exclude isolated background regions and enforce label consistency, and put forward a hybrid interactive segmentation method, Neutro-Connectedness Cut (NC-Cut), which can overcome the above two problems by utilizing both pixel-wise appearance information and region-based NC properties. We evaluate the proposed NC-Cut by employing two image datasets (265 images), and demonstrate that the proposed approach outperforms state-of-the-art interactive image segmentation methods (Grabcut, MILCut, One-Cut, and pPBC).

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Riverbed: A Novel User-Steered Image Segmentation Method Based on Optimum Boundary Tracking

Cited by 53 publications

References 35 publications

Combination of paths for interactive segmentation

Combination of paths for interactive segmentation

Combination of Piecewise-Geodesic Curves for Interactive Image Segmentation

Neutro-Connectedness Cut

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