Research on Low Quality Texture Image Segmentation Background

机译：低质量纹理图像分割背景研究

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摘要

In image processing, the texture image segmentation is one of the most important issues. Considering the problem that the traditional segmentation methods often fail to the low quality texture image segmentation, this paper proposes a modified OTSU thresholding segmentation method. Experimental results show that the proposed method not only is well adapt to the change of brightness and contrast, but also can be applied to much complex background.

机译：在图像处理中，纹理图像分割是最重要的问题之一。考虑到传统分割方法常常无法低质量纹理图像分割的问题，本文提出了一种修改的OTSU阈值分割方法。实验结果表明，该方法不仅适应亮度和对比度的变化，还可以应用于许多复杂的背景。

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《International Conference on Manufacturing Technology and Electronics Applications》|2014年||共4页
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作者
Ning Liu; Hongxia Wang;
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中图分类 TH16-53;
关键词
Texture image; Image segmentation; Thresholding; OTSU method;

机译：纹理图像;图像分割;阈值;OTSU方法;

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专利

1. Mean Field Decomposition of A Posteriori Probability for MRF-Based Image Segmentation: Unsupervised Multispectral Textured Image Segmentation [J] . Hideki NODA, Mehdi N. SHIRAZI, Nobuteru TAKAO IEICE Transactions on Information and Systems . 1999,第12期

机译：基于MRF的图像分割的后验概率平均场分解：无监督多光谱纹理图像分割
2. An Effective Segmentation Pattern Using Multi-class Independent Component Analysis on High Quality Color Texture Images [J] . N. Balakrishnan, S.P. Shantharajah Research journal of applied science, engineering and technology . 2016,第9期

机译：使用多类独立成分分析的高质量彩色纹理图像有效分割模式
3. Fast segmentation of industrial quality pavement images using Laws texture energy measures and k-means clustering [J] . Mathavan Senthan, Kumar Akash, Kamal Khurram, Journal of electronic imaging . 2016,第5期

机译：使用Laws纹理能量测度和k均值聚类快速分割工业质量路面图像
4. Research on Low Quality Texture Image Segmentation Background [C] . Ning Liu, Hongxia Wang International Conference on Manufacturing Technology and Electronics Applications . 2014

机译：低质量纹理图像分割背景研究
5. Unsupervised segmentation of noisy and textured images modeled by Markov random fields. [D] . Gregoriou, Georghios Kyriacos. 1992

机译：由Markov随机场建模的噪点和纹理图像的无监督分割。
6. Unsupervised background-constrained tank segmentation of infrared images in complex background based on the Otsu method [O] . Yulong Zhou, Min Gao, Dan Fang, -1

机译：基于Otsu方法的复杂背景下无监督背景下红外图像坦克分割
7. Classification Of Textured And Non-Textured Images Using Region Segmentation [O] . Jia Li, James Ze Wang, Gio Wiederhold 2000

机译：使用区域分割对纹理和非纹理图像进行分类

Research on Low Quality Texture Image Segmentation Background

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