Sampling Shape Contours Using Optimization over a Geometric Graph

Kazuya OSE; Kazunori IWATA; Nobuo SUEMATSU

doi:10.1587/transinf.2018EDP7353

Sampling Shape Contours Using Optimization over a Geometric Graph

Kazuya OSE, Kazunori IWATA, Nobuo SUEMATSU

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Consider selecting points on a contour in the x-y plane. In shape analysis, this is frequently referred to as contour sampling. It is important to select the points such that they effectively represent the shape of the contour. Generally, the stroke order and number of strokes are informative for that purpose. Several effective methods exist for sampling contours drawn with a certain stroke order and number of strokes, such as the English alphabet or Arabic figures. However, many contours entail an uncertain stroke order and number of strokes, such as pictures of symbols, and little research has focused on methods for sampling such contours. This is because selecting the points in this case typically requires a large computational cost to check all the possible choices. In this paper, we present a sampling method that is useful regardless of whether the contours are drawn with a certain stroke order and number of strokes or not. Our sampling method thereby expands the application possibilities of contour processing. We formulate contour sampling as a discrete optimization problem that can be solved using a type of direct search. Based on a geometric graph whose vertices are the points and whose edges form rectangles, we construct an effective objective function for the problem. Using different shape datasets, we demonstrate that our sampling method is effective with respect to shape representation and retrieval.

Publication: IEICE TRANSACTIONS on Information Vol.E102-D No.12 pp.2547-2556

Publication Date: 2019/12/01

Publicized: 2019/09/11

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2018EDP7353

Type of Manuscript: PAPER

Category: Pattern Recognition

Authors

Kazuya OSE
  Hiroshima City University
Kazunori IWATA
  Hiroshima City University
Nobuo SUEMATSU
  Hiroshima City University

Keyword

contour sampling, shape representation, shape retrieval, geometric graph

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Kazuya OSE, Kazunori IWATA, Nobuo SUEMATSU, "Sampling Shape Contours Using Optimization over a Geometric Graph" in IEICE TRANSACTIONS on Information, vol. E102-D, no. 12, pp. 2547-2556, December 2019, doi: 10.1587/transinf.2018EDP7353.
Abstract: Consider selecting points on a contour in the x-y plane. In shape analysis, this is frequently referred to as contour sampling. It is important to select the points such that they effectively represent the shape of the contour. Generally, the stroke order and number of strokes are informative for that purpose. Several effective methods exist for sampling contours drawn with a certain stroke order and number of strokes, such as the English alphabet or Arabic figures. However, many contours entail an uncertain stroke order and number of strokes, such as pictures of symbols, and little research has focused on methods for sampling such contours. This is because selecting the points in this case typically requires a large computational cost to check all the possible choices. In this paper, we present a sampling method that is useful regardless of whether the contours are drawn with a certain stroke order and number of strokes or not. Our sampling method thereby expands the application possibilities of contour processing. We formulate contour sampling as a discrete optimization problem that can be solved using a type of direct search. Based on a geometric graph whose vertices are the points and whose edges form rectangles, we construct an effective objective function for the problem. Using different shape datasets, we demonstrate that our sampling method is effective with respect to shape representation and retrieval.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2018EDP7353/_p

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@ARTICLE{e102-d_12_2547,
author={Kazuya OSE, Kazunori IWATA, Nobuo SUEMATSU, },
journal={IEICE TRANSACTIONS on Information},
title={Sampling Shape Contours Using Optimization over a Geometric Graph},
year={2019},
volume={E102-D},
number={12},
pages={2547-2556},
abstract={Consider selecting points on a contour in the x-y plane. In shape analysis, this is frequently referred to as contour sampling. It is important to select the points such that they effectively represent the shape of the contour. Generally, the stroke order and number of strokes are informative for that purpose. Several effective methods exist for sampling contours drawn with a certain stroke order and number of strokes, such as the English alphabet or Arabic figures. However, many contours entail an uncertain stroke order and number of strokes, such as pictures of symbols, and little research has focused on methods for sampling such contours. This is because selecting the points in this case typically requires a large computational cost to check all the possible choices. In this paper, we present a sampling method that is useful regardless of whether the contours are drawn with a certain stroke order and number of strokes or not. Our sampling method thereby expands the application possibilities of contour processing. We formulate contour sampling as a discrete optimization problem that can be solved using a type of direct search. Based on a geometric graph whose vertices are the points and whose edges form rectangles, we construct an effective objective function for the problem. Using different shape datasets, we demonstrate that our sampling method is effective with respect to shape representation and retrieval.},
keywords={},
doi={10.1587/transinf.2018EDP7353},
ISSN={1745-1361},
month={December},}

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TY - JOUR
TI - Sampling Shape Contours Using Optimization over a Geometric Graph
T2 - IEICE TRANSACTIONS on Information
SP - 2547
EP - 2556
AU - Kazuya OSE
AU - Kazunori IWATA
AU - Nobuo SUEMATSU
PY - 2019
DO - 10.1587/transinf.2018EDP7353
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E102-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2019
AB - Consider selecting points on a contour in the x-y plane. In shape analysis, this is frequently referred to as contour sampling. It is important to select the points such that they effectively represent the shape of the contour. Generally, the stroke order and number of strokes are informative for that purpose. Several effective methods exist for sampling contours drawn with a certain stroke order and number of strokes, such as the English alphabet or Arabic figures. However, many contours entail an uncertain stroke order and number of strokes, such as pictures of symbols, and little research has focused on methods for sampling such contours. This is because selecting the points in this case typically requires a large computational cost to check all the possible choices. In this paper, we present a sampling method that is useful regardless of whether the contours are drawn with a certain stroke order and number of strokes or not. Our sampling method thereby expands the application possibilities of contour processing. We formulate contour sampling as a discrete optimization problem that can be solved using a type of direct search. Based on a geometric graph whose vertices are the points and whose edges form rectangles, we construct an effective objective function for the problem. Using different shape datasets, we demonstrate that our sampling method is effective with respect to shape representation and retrieval.
ER -