NDLI: Automatic target segmentation based on texture for microscopic images of Chinese herbal powders

Content Provider	IEEE Xplore Digital Library
Author	Jun Li Yixu Song Yaoli Li Shaoqin Cai Zehong Yang
Copyright Year	2013
Description	Author affiliation: Comput. Sci. & Technol. Dept., Tsinghua Univ., Beijing, China (Jun Li; Yixu Song; Zehong Yang) \|\| Sch. of Pharm. Sci., Peking Univ., Beijing, China (Yaoli Li; Shaoqin Cai)
Abstract	The identification of Chinese herbal powders is usually based on physical or chemical detection, but that is far from enough to identity dozens of herbal species. Microscopic images of these powders contain variety of information, and important evidence for identification. These images usually contain variety of substance, and most of them are noises, which makes the target segmentation become a difficult job. 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, feature vector of texture is extracted 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 used to test our method: microscopic images of Chinese herbal powders, Brodaze Images, and natural texture images. 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.
Sponsorship	IEEE Control Syst. Soc.
Starting Page	1473
Ending Page	1478
File Size	615656
Page Count	6
File Format	PDF
ISBN	9781467355339
e-ISBN	9781467355346
DOI	10.1109/CCDC.2013.6561159
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Powders Microscopy Image edge detection Chinese herbal powder Noise Feature extraction texture feature Vectors microscopic images automatic segmentation
Content Type	Text
Resource Type	Article

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