An improved topology extraction approach for vectorization of sketchy line drawings

Chen, Jiazhou; Du, Mengqi; Qin, Xujia; Miao, Yongwei

doi:10.1007/s00371-018-1549-z

Cited by 16 publications

(13 citation statements)

References 30 publications

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“…There are different skeletonization methods depending on a type of input data. Morphological thinning techniques are extensively used for computing the skeleton of a binary image [11][12][13]. They allow us to obtain a pixel-based representation of the skeleton.…”

Section: Related Workmentioning

confidence: 99%

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An Optimized Algorithm for Computing the Voronoi Skeleton

Kotsur¹,

Tereshchenko²

2020

IJC

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The skeleton-based representation is widely used in such fields as computer graphics, computer vision and image processing. Therefore, efficient algorithms for computing planar skeletons are of high relevance. In this paper, we propose an optimized algorithm for computing the Voronoi skeleton of a planar object with holes, which is represented by a set of polygons. Such skeleton allows us to use efficiently the properties of the underlying Voronoi diagram data structure. It was shown that the complexity of the proposed Voronoi-based skeletonization algorithm is O(N log N), where N is the number of polygon’s vertices. We have also proposed theoretically justified optimization heuristic based on polygon/polyline simplification algorithms. In order to evaluate and prove the efficiency of the heuristic, a series of computational experiments were conducted involving the polygons obtained from MPEG 7 CE-Shape-1 dataset. We have measured the execution time of the skeletonization algorithm, computational overheads related to the introduced heuristics and also the influence of the heuristic onto accuracy of the resulting skeleton. As a result, we have established the criteria, which allow us to choose the optimal heuristics for our skeletonization algorithm depending on the system’s requirements.

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Section: Related Workmentioning

confidence: 99%

“…They allow us to obtain a pixel-based representation of the skeleton. In order to obtain the topology of the underlying graph, graph vectorization methods can be applied [14,15].…”

Section: Related Workmentioning

confidence: 99%

An Optimized Algorithm for Computing the Voronoi Skeleton

Kotsur¹,

Tereshchenko²

2020

IJC

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“…Several approaches have been proposed to extract simplified drawings from scanning pencil sketches [5,22,[30][31][32][33][34]. Such approaches are built directly upon overtraced strokes for line drawing creation because strokes are blended "for free" as the user draws [19].…”

Section: Related Workmentioning

confidence: 99%

“…Favreau et al [22] proposed the first vectorization algorithm that explicitly balances fidelity to the input bitmap with simplicity output, as measured by the number of curves and their degree. Chen et al [33] presented an improved topology extraction approach for vectorization of crude line drawings. It was proved to be efficient and robust but lacked high-level understanding of the line drawing.…”

Section: Related Workmentioning

confidence: 99%

Tolerance Zone-Based Grouping Method for Online Multiple Overtracing Freehand Sketches

Wang

et al. 2020

Mathematical Problems in Engineering

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Multiple overtracing strokes are common drawing behaviors in freehand sketching; that is, additional strokes are often drawn repeatedly over the existing ones to add more details. This paper proposes a method based on stroke-tolerance zones to group multiple overtraced strokes which are drawn to express a 2D primitive, aiming to convert online freehand sketches into 2D line drawings, which is a base for further 3D reconstruction. Firstly, after the user inputs a new stroke, a tolerance zone around the stroke is constructed by reference to its polygonal approximation points obtained from the stroke preprocessing. Then, the input strokes are divided into stroke groups, each representing a primitive through the stroke grouping process based on the overtraced ratio of two strokes. At last, each stroke group is fitted into one or more 2D geometric primitives including line segments, polylines, ellipses, and arcs. The proposed method groups two strokes together based on their screen-space proximity directly instead of classifying and fitting them firstly, so that it can group strokes of arbitrary shapes. A sketch-recognition prototype system has been implemented to test the effectiveness of the proposed method. The results showed that the proposed method could support online multiple overtracing freehand sketching with no limitation on drawing sequence, but it only deals with strokes with relatively high overtraced ratio.

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“…Many approaches have been proposed to extract simplified drawings from scanned pencil sketches [1,[27][28][29][30][31][32][33][34][35][36]. Kara et al [28] proposed a sketch recognizer that allows overtracing symbol input, but it relies entirely on the symbol libraries where the sketch is examined in pixels; hence, no work has been done on the interpretation of individual strokes.…”

Section: Related Workmentioning

confidence: 99%

Multistroke Grouping of Online Freehand Axonometric Sketches for Mechanical Models

Wang

2020

Mathematical Problems in Engineering

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Multistroke drawing occurs frequently in conceptual design sketches; however, it is almost unsupported by the current sketch-based user interfaces. We proposed a sketch recognition system based on the multistroke primitive grouping method. Based on grouping the strokes that lie within the mutual boundaries between adjacent regions, we create line drawings from online freehand axonometric sketches of mechanical models. First, closed regions and their boundary bands of the sketch were extracted. Then, the strokes that cross the boundary bands of two or more closed regions are segmented, and the strokes that lie within the intersection of two adjacent boundary bands are grouped. Finally, grouped strokes are simplified into a new single stroke and then fitted as a geometric primitive; thus, the input sketches are recognized to the line drawings. We developed a prototype of the sketch recognition system to evaluate the proposed method. The results showed that the input sketches are simplified into the accurate line drawings efficiently. The proposed method can be applied to both multistroke overtracing and nonovertracing sketches.

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An improved topology extraction approach for vectorization of sketchy line drawings

Cited by 16 publications

References 30 publications

An Optimized Algorithm for Computing the Voronoi Skeleton

An Optimized Algorithm for Computing the Voronoi Skeleton

Tolerance Zone-Based Grouping Method for Online Multiple Overtracing Freehand Sketches

Multistroke Grouping of Online Freehand Axonometric Sketches for Mechanical Models

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