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学科主题: 药学
题名:
Automatic Target Segmentation based on Texture for Microscopic Images of Natural Medical Herbal Powders
作者: Li, Jun1; Song, Yi-Xu1; Li, Yao-Li2; Cai, Shao-Qing2; Yang, Ze-Hong1
关键词: Medical herbal powder ; Microscopic images ; Automatic segmentation ; Texture feature
刊名: JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY
发表日期: 2015-02-01
DOI: 10.1007/s11265-013-0839-y
卷: 78, 期:2, 页:139-146
收录类别: SCI
文章类型: Article
WOS标题词: Science & Technology
类目[WOS]: Computer Science, Information Systems ; Engineering, Electrical & Electronic
研究领域[WOS]: Computer Science ; Engineering
英文摘要:

The authentication of natural medical herbs has crucial impact on the clinical curative effect. Much of these herbs have been ground into powders in the market, leading to the difficulty of identification. Microscopic images of these powders contain important evidences for identification. Currently identification based on these microscopic images are mostly conducted by manual observation. Identification aided by computer vision technique is an important research subject recently. These microscopic images usually contain variety of substance, and most of them are noises, thus the target segmentation is necessary for identification. An effective automatic target segmentation algorithm based on texture is proposed in this paper. Our method consists of two steps: "Preliminary Segmentation" and "Further Segmentation". Firstly, gradient transform and image fusion are conducted for image preprocessing, then each pixel is encoded into a feature vector based on texture and clustered into two groups: background and foreground. Secondly, taking the continuity of edge and the locality of target into consideration, energy equations are established, and maximum flow-minimum cut algorithm is applied to solve them. Three groups of images are tested to evaluate our method, and the experimental results show that our method achieves a better segmentation compared with Grab-Cut, and additionally user inter-action is not required in our method.

语种: 英语
WOS记录号: WOS:000348998900004
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.bjmu.edu.cn/handle/400002259/64981
Appears in Collections:北京大学药学院_期刊论文

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作者单位: 1.Tsinghua Univ, State Key Lab Intelligent Technol & Syst, Tsinghua Natl Lab Informat Sci & Technol, Comp Sci & Technol Dept, Beijing 100084, Peoples R China
2.Peking Univ, State Key Lab Nat & Biol Drugs, Sch Pharmaceut Sci, Beijing 100191, Peoples R China

Recommended Citation:
Li, Jun,Song, Yi-Xu,Li, Yao-Li,et al. Automatic Target Segmentation based on Texture for Microscopic Images of Natural Medical Herbal Powders[J]. JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY,2015,78(2):139-146.
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