Image segmentation based on 2D Otsu method with histogram analysis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

143 Citations (Scopus)

Abstract

Image segmentation plays an important role in image analysis and computer vision system. Among all segmentation techniques, the automatic thresholding methods are widely used because of their advantages of simple implement and time saving. Otsu method is one of thresholding methods and frequently used in various fields. Two-dimensional (2D) Otsu method behaves well in segmenting images of low signal-to-noise ratio than one-dimensional (1D). But it gives satisfactory results only when the numbers of pixels in each class are close to each other. Otherwise, it gives the improper results. In this paper, 2D histogram projection is used to correct the Otsu threshold. The 1D histograms are acquired by 2D histogram projection in x and y axes and a fast algorithm for searching the extrema of the projected histogram is proposed based on the wavelet transform in this paper. Experimental results show that the proposed method performs better than the traditional Otsu method for our renal biopsy samples.

Original languageEnglish
Title of host publicationProceedings - International Conference on Computer Science and Software Engineering, CSSE 2008
Pages105-108
Number of pages4
Volume6
DOIs
Publication statusPublished - 2008
EventInternational Conference on Computer Science and Software Engineering, CSSE 2008 - Wuhan, Hubei
Duration: 2008 Dec 122008 Dec 14

Other

OtherInternational Conference on Computer Science and Software Engineering, CSSE 2008
CityWuhan, Hubei
Period08/12/1208/12/14

Fingerprint

Biopsy
Image segmentation
Wavelet transforms
Image analysis
Computer vision
Signal to noise ratio
Pixels

Keywords

  • 2D histogram projection
  • 2D Otsu method
  • Image segmentation
  • Wavelet transform

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Software

Cite this

Jun, Z., & Furuzuki, T. (2008). Image segmentation based on 2D Otsu method with histogram analysis. In Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008 (Vol. 6, pp. 105-108). [4723207] https://doi.org/10.1109/CSSE.2008.206

Image segmentation based on 2D Otsu method with histogram analysis. / Jun, Zhang; Furuzuki, Takayuki.

Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008. Vol. 6 2008. p. 105-108 4723207.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jun, Z & Furuzuki, T 2008, Image segmentation based on 2D Otsu method with histogram analysis. in Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008. vol. 6, 4723207, pp. 105-108, International Conference on Computer Science and Software Engineering, CSSE 2008, Wuhan, Hubei, 08/12/12. https://doi.org/10.1109/CSSE.2008.206
Jun Z, Furuzuki T. Image segmentation based on 2D Otsu method with histogram analysis. In Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008. Vol. 6. 2008. p. 105-108. 4723207 https://doi.org/10.1109/CSSE.2008.206
Jun, Zhang ; Furuzuki, Takayuki. / Image segmentation based on 2D Otsu method with histogram analysis. Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008. Vol. 6 2008. pp. 105-108
@inproceedings{d9477f286afd471a938614b95c532f9c,
title = "Image segmentation based on 2D Otsu method with histogram analysis",
abstract = "Image segmentation plays an important role in image analysis and computer vision system. Among all segmentation techniques, the automatic thresholding methods are widely used because of their advantages of simple implement and time saving. Otsu method is one of thresholding methods and frequently used in various fields. Two-dimensional (2D) Otsu method behaves well in segmenting images of low signal-to-noise ratio than one-dimensional (1D). But it gives satisfactory results only when the numbers of pixels in each class are close to each other. Otherwise, it gives the improper results. In this paper, 2D histogram projection is used to correct the Otsu threshold. The 1D histograms are acquired by 2D histogram projection in x and y axes and a fast algorithm for searching the extrema of the projected histogram is proposed based on the wavelet transform in this paper. Experimental results show that the proposed method performs better than the traditional Otsu method for our renal biopsy samples.",
keywords = "2D histogram projection, 2D Otsu method, Image segmentation, Wavelet transform",
author = "Zhang Jun and Takayuki Furuzuki",
year = "2008",
doi = "10.1109/CSSE.2008.206",
language = "English",
isbn = "9780769533360",
volume = "6",
pages = "105--108",
booktitle = "Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008",

}

TY - GEN

T1 - Image segmentation based on 2D Otsu method with histogram analysis

AU - Jun, Zhang

AU - Furuzuki, Takayuki

PY - 2008

Y1 - 2008

N2 - Image segmentation plays an important role in image analysis and computer vision system. Among all segmentation techniques, the automatic thresholding methods are widely used because of their advantages of simple implement and time saving. Otsu method is one of thresholding methods and frequently used in various fields. Two-dimensional (2D) Otsu method behaves well in segmenting images of low signal-to-noise ratio than one-dimensional (1D). But it gives satisfactory results only when the numbers of pixels in each class are close to each other. Otherwise, it gives the improper results. In this paper, 2D histogram projection is used to correct the Otsu threshold. The 1D histograms are acquired by 2D histogram projection in x and y axes and a fast algorithm for searching the extrema of the projected histogram is proposed based on the wavelet transform in this paper. Experimental results show that the proposed method performs better than the traditional Otsu method for our renal biopsy samples.

AB - Image segmentation plays an important role in image analysis and computer vision system. Among all segmentation techniques, the automatic thresholding methods are widely used because of their advantages of simple implement and time saving. Otsu method is one of thresholding methods and frequently used in various fields. Two-dimensional (2D) Otsu method behaves well in segmenting images of low signal-to-noise ratio than one-dimensional (1D). But it gives satisfactory results only when the numbers of pixels in each class are close to each other. Otherwise, it gives the improper results. In this paper, 2D histogram projection is used to correct the Otsu threshold. The 1D histograms are acquired by 2D histogram projection in x and y axes and a fast algorithm for searching the extrema of the projected histogram is proposed based on the wavelet transform in this paper. Experimental results show that the proposed method performs better than the traditional Otsu method for our renal biopsy samples.

KW - 2D histogram projection

KW - 2D Otsu method

KW - Image segmentation

KW - Wavelet transform

UR - http://www.scopus.com/inward/record.url?scp=79951472722&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79951472722&partnerID=8YFLogxK

U2 - 10.1109/CSSE.2008.206

DO - 10.1109/CSSE.2008.206

M3 - Conference contribution

SN - 9780769533360

VL - 6

SP - 105

EP - 108

BT - Proceedings - International Conference on Computer Science and Software Engineering, CSSE 2008

ER -