A systolic algorithm for Euclidean distance transform

Miyazawa, Miyuki; Zeng, Peifeng; Iso, Nozomi; Hirata, T.

doi:10.1109/tpami.2006.133

Cited by 10 publications

(8 citation statements)

References 16 publications

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“…All these innovations reduce the computational complexity significantly. A parallel version of PBEDT can be easily implemented [18] [21]. This algorithm can also be extended to three or higher dimensional binary images.…”

Section: Resultsmentioning

confidence: 99%

Efficient Euclidean distance transform using perpendicular bisector segmentation

Wang

Tan

2011

CVPR 2011

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In this paper, we propose an efficient algorithm for computing the Euclidean distance transform of two-dimensional binary image, called PBEDT (Perpendicular Bisector Euclidean Distance Transform). PBEDT is a two-stage independent scan algorithm. In the first stage, PBEDT computes the distance from each point to its closest feature point in the same column using one time column-wise scan. In the second stage, PBEDT computes the distance transform for each point by row with intermediate results of the previous stage. By using the geometric properties of the perpendicular bisector, PBEDT directly computes the segmentation by feature points for each row and each segment corresponding to one feature point. Furthermore, by using integer arithmetic to avoid time consuming float operations, PBEDT still achieves exact results. All these methods reduce the computational complexity significantly. Consequently, an efficient and exact linear time Euclidean distance transform algorithm is implemented. Detailed comparison with state-of-the-art linear time Euclidean distance transform algorithms shows that PBEDT is the fastest on most cases, and also the most stable one with respect to image contents.

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Section: Resultsmentioning

confidence: 99%

Efficient Euclidean distance transform using perpendicular bisector segmentation

Wang

Tan

2011

CVPR 2011

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“…For example, given two frame images, according to the color histogram difference value , i j DF , texture similarity f and edge histogram H, the overall similarity of two image can be calculated. Further, by the Euclidean distance [9] , the color histogram similarity d 1 , texture similarity d 2 and edge histogram d 3 between the two frame images can be calculated.…”

Section: A Feature Fusionmentioning

confidence: 99%

Shot Boundary Detection Algorithm Based on Multi-Feature Fusion

Jin

Hong

Feng

et al. 2013

AMM

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To establish a general and robust shot boundary detection algorithm, according to characteristics of lens conversion and the ideal of multiple video features fusion, a shot boundary detection algorithm is proposed based on YUV histogram, texture feature and edge orientation histogram in the paper. Besides, global and self-adaptive threshold are combined to use so as to control the process of shot boundary detection and enhance the accuracy of threshold selection. The experiment results show that the algorithm can effectively realize video shot boundary detection and strengthen the robustness of the detection.

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“…'Preliminary versions of the systolic algorithms for Ti and T2 have appeared in [11]. at cell Co one by one in this order.…”

Section: Algorithm For Timentioning

confidence: 99%

3-D Voronoi tessellation algorithms

Hirata

2005

Japan J. Indust. Appl. Math.

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We consider the discrete Voronoi diagram in the three-dimensional space, that is, the Voronoi tessellation of a 3-D binary image. The input to the tessellation algorithm is a 3-D image containing a set of pixels of value 0 (generators). The goal is to classify the rest of the pixels to the nearest generator. This paper gives a simple algorithm for computing the Voronoi tessellation map of a 3-D binary image. It runs in O(N 3 ) time for an N x N x N input image. A hardware algorithm is also presented, which computes the 3-D Voronoi tessellation map in O(N 2 ) time on an 0(N 3 )-cell array.

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A systolic algorithm for Euclidean distance transform

Cited by 10 publications

References 16 publications

Efficient Euclidean distance transform using perpendicular bisector segmentation

Efficient Euclidean distance transform using perpendicular bisector segmentation

Shot Boundary Detection Algorithm Based on Multi-Feature Fusion

3-D Voronoi tessellation algorithms

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