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A new approach for robust segmentation of the noisy or textured images
Wang ZZ(王振洲)
作者部门机器人学研究室
关键词Segmentation Labeled Pixel Spatial Density Distribution Slope Difference Distribution Histogram Distribution
发表期刊SIAM Journal on Imaging Sciences
ISSN1936-4954
2016
卷号9期号:3页码:1409-1436
收录类别SCI ; EI
EI收录号20164102880690
WOS记录号WOS:000385277200021
产权排序1
资助机构Chinese Academy of Sciences (CAS), Y5A1270101.
摘要Segmentation of noisy or textured images remains challenging in both accuracy and computational efficiency. In this paper, we propose a new approach for segmentation of noisy or textured images that exist widely in real life. The proposed approach finds the mean values of different pixel classes more efficiently and accurately than the benchmark expectation maximization (EM) and K-means methods. With these mean values, the segmentation is achieved by clustering the pixels to its nearest mean. When too much noise is left for the presegmentation result or when textured objects are involved, we propose transforming the density distribution of labeled pixels into grayscale distribution by down-sampling the image with a bicubic function. An optimal threshold is automatically selected from the slope difference distribution of the histogram for the final segmentation. The extracted boundary is then refined by an energy minimization function with the detected edges when enough clear edges can be obtained. A large variety of images are used to validate the proposed approach, and the results verify its effectiveness in segmenting both noisy and textured images.
语种英语
WOS标题词Science & Technology ; Technology ; Physical Sciences
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Software Engineering ; Mathematics, Applied ; Imaging Science & Photographic Technology
关键词[WOS]LEVEL SET METHOD ; AURORAL OVAL SEGMENTATION ; ACTIVE CONTOURS ; RANDOM-FIELDS
WOS研究方向Computer Science ; Mathematics ; Imaging Science & Photographic Technology
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/19254
专题机器人学研究室
通讯作者Wang ZZ(王振洲)
作者单位State Key Laboratory of Robotics at Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang City, China
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GB/T 7714
Wang ZZ. A new approach for robust segmentation of the noisy or textured images[J]. SIAM Journal on Imaging Sciences,2016,9(3):1409-1436.
APA Wang ZZ.(2016).A new approach for robust segmentation of the noisy or textured images.SIAM Journal on Imaging Sciences,9(3),1409-1436.
MLA Wang ZZ."A new approach for robust segmentation of the noisy or textured images".SIAM Journal on Imaging Sciences 9.3(2016):1409-1436.
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