Segmentation of wood surface knots and wormholes based on an improved LBF Model

BAI Xuebing; XU Jingtao; GUO Jingqiu; CHEN Kai

doi:10.11833/j.issn.2095-0756.2016.02.017

Volume 33 Issue 2

Mar. 2016

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BAI Xuebing, XU Jingtao, GUO Jingqiu, CHEN Kai. Segmentation of wood surface knots and wormholes based on an improved LBF Model[J]. Journal of Zhejiang A&F University, 2016, 33(2): 306-314. doi: 10.11833/j.issn.2095-0756.2016.02.017

Citation:

BAI Xuebing, XU Jingtao, GUO Jingqiu, CHEN Kai. Segmentation of wood surface knots and wormholes based on an improved LBF Model[J]. Journal of Zhejiang A&F University, 2016, 33(2): 306-314. doi: 10.11833/j.issn.2095-0756.2016.02.017

Segmentation of wood surface knots and wormholes based on an improved LBF Model

doi: 10.11833/j.issn.2095-0756.2016.02.017

1.
College of Machinery Electricity, Northeast Forestry University, Harbin 150040, Heilongjiang, China

Funds:

黑龙江省自然科学基金资助项目（C201208）

Received Date: 2015-04-20
Rev Recd Date: 2015-09-16
Publish Date: 2016-04-20

Abstract

To make wood surface defect segmentation faster and more effective, research was conducted to put forward an improved LBF （local binary fitting） Model with image segmentation based on the Chan-Vese （CV） Model. The improved LBF Model added a new level set formulation with a linear regularization term, and at the same time formed a Gaussian function as the kernel function with two local values for fitting energy. Results showed that the improved algorithm could overcome the segmentation shortcomings in the LBF Model. Also, the segmentation process was not sensitive to the size or the position of the initial contour. However, the anti noise of the algorithm was enhanced, and the image could be segmented in non-uniform gray. The experiment showed that the algorithm completely extracted the wood surface defect images with single and multi objectives, and level set evolution corresponding to the defect image could be obtained. ［Ch, 21 fig, 1 tab. 15 ref.］
- wood science and technology,
- wood surface defects,
- wood image segmentation,
- LBF model,
- level set

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通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

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Segmentation of wood surface knots and wormholes based on an improved LBF Model

1. College of Machinery Electricity, Northeast Forestry University, Harbin 150040, Heilongjiang, China

Funds:

黑龙江省自然科学基金资助项目（C201208）

Received Date: 2015-04-20

Rev Recd Date: 2015-09-16

Publish Date: 2016-04-20

Key words:

Abstract: To make wood surface defect segmentation faster and more effective, research was conducted to put forward an improved LBF （local binary fitting） Model with image segmentation based on the Chan-Vese （CV） Model. The improved LBF Model added a new level set formulation with a linear regularization term, and at the same time formed a Gaussian function as the kernel function with two local values for fitting energy. Results showed that the improved algorithm could overcome the segmentation shortcomings in the LBF Model. Also, the segmentation process was not sensitive to the size or the position of the initial contour. However, the anti noise of the algorithm was enhanced, and the image could be segmented in non-uniform gray. The experiment showed that the algorithm completely extracted the wood surface defect images with single and multi objectives, and level set evolution corresponding to the defect image could be obtained. ［Ch, 21 fig, 1 tab. 15 ref.］

Segmentation of wood surface knots and wormholes based on an improved LBF Model

doi: 10.11833/j.issn.2095-0756.2016.02.017

Abstract

References

Proportional views

通讯作者: 陈斌, bchen63@163.com

Related

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