An Algorithm of Connecting Broken Objects Based on the Skeletons

Chao XU; Dongxiang ZHOU; Yunhui LIU

doi:10.1587/transinf.2016EDL8117

An Algorithm of Connecting Broken Objects Based on the Skeletons

Chao XU, Dongxiang ZHOU, Yunhui LIU

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Summary :

The segmentation of Mycobacterium tuberculosis images forms the basis for the computer-aided diagnosis of tuberculosis. The segmented objects are often broken due to the low-contrast objects and the limits of segmentation method. This will result in decreasing the accuracy of segmentation and recognition. A simple and effective post-processing method is proposed to connect the broken objects. The broken objects in the segmented binary images are connected based on the information obtained from their skeletons. Experimental results demonstrate the effectiveness of our proposed method.

Publication: IEICE TRANSACTIONS on Information Vol.E99-D No.11 pp.2832-2835

Publication Date: 2016/11/01

Publicized: 2016/08/10

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2016EDL8117

Type of Manuscript: LETTER

Category: Pattern Recognition

Authors

Chao XU
  National University of Defense Technology
Dongxiang ZHOU
  National University of Defense Technology
Yunhui LIU
  The Chinese University of Hong Kong

Keyword

segmentation, tuberculosis, computer-aided diagnosis, post processing

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Chao XU, Dongxiang ZHOU, Yunhui LIU, "An Algorithm of Connecting Broken Objects Based on the Skeletons" in IEICE TRANSACTIONS on Information, vol. E99-D, no. 11, pp. 2832-2835, November 2016, doi: 10.1587/transinf.2016EDL8117.
Abstract: The segmentation of Mycobacterium tuberculosis images forms the basis for the computer-aided diagnosis of tuberculosis. The segmented objects are often broken due to the low-contrast objects and the limits of segmentation method. This will result in decreasing the accuracy of segmentation and recognition. A simple and effective post-processing method is proposed to connect the broken objects. The broken objects in the segmented binary images are connected based on the information obtained from their skeletons. Experimental results demonstrate the effectiveness of our proposed method.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.2016EDL8117/_p

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@ARTICLE{e99-d_11_2832,
author={Chao XU, Dongxiang ZHOU, Yunhui LIU, },
journal={IEICE TRANSACTIONS on Information},
title={An Algorithm of Connecting Broken Objects Based on the Skeletons},
year={2016},
volume={E99-D},
number={11},
pages={2832-2835},
abstract={The segmentation of Mycobacterium tuberculosis images forms the basis for the computer-aided diagnosis of tuberculosis. The segmented objects are often broken due to the low-contrast objects and the limits of segmentation method. This will result in decreasing the accuracy of segmentation and recognition. A simple and effective post-processing method is proposed to connect the broken objects. The broken objects in the segmented binary images are connected based on the information obtained from their skeletons. Experimental results demonstrate the effectiveness of our proposed method.},
keywords={},
doi={10.1587/transinf.2016EDL8117},
ISSN={1745-1361},
month={November},}

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TY - JOUR
TI - An Algorithm of Connecting Broken Objects Based on the Skeletons
T2 - IEICE TRANSACTIONS on Information
SP - 2832
EP - 2835
AU - Chao XU
AU - Dongxiang ZHOU
AU - Yunhui LIU
PY - 2016
DO - 10.1587/transinf.2016EDL8117
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2016
AB - The segmentation of Mycobacterium tuberculosis images forms the basis for the computer-aided diagnosis of tuberculosis. The segmented objects are often broken due to the low-contrast objects and the limits of segmentation method. This will result in decreasing the accuracy of segmentation and recognition. A simple and effective post-processing method is proposed to connect the broken objects. The broken objects in the segmented binary images are connected based on the information obtained from their skeletons. Experimental results demonstrate the effectiveness of our proposed method.
ER -