Simulating the grassfire transform using an active contour model

Leymarie, Frederic Fol; Levine, Martin D.

doi:10.1109/34.107013

Cited by 225 publications

(104 citation statements)

References 54 publications

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“…Ranwez and Soille (2002) propose an order independent scheme. Anchor points have previously been used, for example by Leymarie and Levine (1992). They use an active contour based approach to determine the medial axis of an object.…”

Section: Introductionmentioning

confidence: 99%

Area-Based Medial Axis of Planar Curves

Niethammer

Betelú

Sapiro

et al. 2004

International Journal of Computer Vision

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A new definition of affine invariant medial axis of planar closed curves is introduced. A point belongs to the affine medial axis if and only if it is equidistant from at least two points of the curve, with the distance being a minimum and given by the areas between the curve and its corresponding chords. The medial axis is robust, eliminating the need for curve denoising. In a dynamical interpretation of this affine medial axis, the medial axis points are the affine shock positions of the affine erosion of the curve. We propose a simple method to compute the medial axis and give examples. We also demonstrate how to use this method to detect affine skew symmetry in real images.

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Section: Introductionmentioning

confidence: 99%

Area-Based Medial Axis of Planar Curves

Niethammer

Betelú

Sapiro

et al. 2004

International Journal of Computer Vision

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“…The goal is to represent an entire protruding sub-structure using one or a few boundary points. Traditionally, such protrusions have a significant contribution in characterising a form's figure [44,30,6,50]. The process of extraction of convex points is similar to the extraction of concave points, the main difference being the value of threshold angle (θ int ), where…”

Section: Interior Convex Pointsmentioning

confidence: 99%

“…Shape representation towards matching has been addressed in many ways by computer scientists in recent years, including by directly characterising and grouping contour points [54,34], by classical contour analysis [6,28,12,50], by computing local contour-based "contexts" [5,56,46,43,55], 1 using instead the inner distance to compute contexts invariant to planar articulations and similar deformations [33,19], using Blum's medial axis transform and its related shock graph to combine geometry and topology with contour and interior symmetries [8,24], or combining explicitly contour and medial axis (aka "skeleton") [30,56,3] (some of the main medial representations are illustrated in Fig. 1, including our proposed method).…”

Section: Introductionmentioning

confidence: 99%

Point-based medialness for 2D shape description and identification

Aparajeya

Leymarie

2015

Multimed Tools Appl

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We propose a perception-based medial point description of a natural form (2D: static or in articulated movement) as a framework for a shape representation which can then be efficiently used in biological species identification and matching tasks. Medialness is defined by adapting and refining a definition first proposed in the cognitive science literature when studying the visual attention of human subjects presented with articulated biological 2D forms in movement, such as horses, dogs and humans (walking, running). In particular, special loci of high medialness for the interior of a form in movement, referred to as "hot spots", prove most attractive to the human perceptual system. We propose an algorithmic process to identify such hot spots. In this article we distinguish exterior from interior shape representation. We further augment hot spots with extremities of medialness ridges identifying significant concavities (from outside) and convexities (from inside). Our representation is strongly footed in results from cognitive psychology, but also inspired by know-how in art and animation, and the algorithmic part is influenced by techniques from more traditional computer vision. A robust shape matching algorithm is designed that finds the most relevant targets from a database of templates by comparing feature points in a scale, rotation and translation invariant way. The performance of our method has been tested on several databases. The robustness of the algorithm is further tested by perturbing the data-set at different levels.

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“…By adding the masks in the Figures 1 and 6, results 14 masks in total, but the last ones can be combined with P 1 , P 2 by means of Boolean operations in order to obtain the masks shown in the Figure 7. Also, A 1 , A 2 , A 3 , A 4 , A 5 , A 6 , A 7 and A 8 , are particular cases of B 1 , B 2 , B 3 y B 4 ; furthermore, if the pixel opposed to the one labeled 1 has value 1 in the masks P 3 , P 4 , P 5 and P 6 , the results are also particular cases of B 1 , B 2 , B 3 , B 4 . These masks include all the possible configurations of end points.…”

Section: Thinning Masksmentioning

confidence: 99%

“…In the former manner, each background pixel takes part on the compute of the skeleton. Thinning algorithms [4,5] and the distance transforms [4,6] belong to this kind of techniques. Most of the more efficient methods are based on thinning techniques.…”

Section: Introductionmentioning

confidence: 99%

Thinning Algorithm to Generate k-Connected Skeletons

León¹,

Yáñez²,

Guzmán³

2004

Lecture Notes in Computer Science

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Abstract. This paper presents a novel algorithm intended to generate kconnected skeletons of a digital binary image using a new mask set. These skeletons may be 4 or 8 connected. The new algorithm performs a thinning process that finish when it is not possible to eliminate additional pixels without breaking the connectivity. The end-point criterion and a 3x3 masks set are used to decide if a pixel is eliminated. The proposed masks set for each kind of connectivity covers all the necessary cases, and guarantee to obtain a one pixel wide and k-connected skeleton without parasitic branches. The new algorithm yields some advantages to developers. It is not just oriented to written characters or some kind of object in particular; this means that the algorithm can be adapted easily to any application generating good results. Besides, the user can work with different classes of connectivity; note that several recent algorithms use 4-connectivity while 8-connectivity is used for others. Additionally, the skeletons produced by the new algorithm are immune to structured noise around the processed objects.

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Simulating the grassfire transform using an active contour model

Abstract: Center for Intelligent Machines. His current research interests include computer vision, mathematical morphology, and biomedical image analysis.

Cited by 225 publications

References 54 publications

Area-Based Medial Axis of Planar Curves

Area-Based Medial Axis of Planar Curves

Point-based medialness for 2D shape description and identification

Thinning Algorithm to Generate k-Connected Skeletons

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