Laser & Optoelectronics Progress, Volume. 50, Issue 12, 121002(2013)

TCM Spectral Imaging Detection Based on Self-Adaptive Region Segmentation Method

Wang Lin1、*, Hu Cuiying2, Pang Qichang3, Ma Ji4, and Cui Daijun3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    We use a segmentation arithmetic of self-adaption to deal with the spectral images of traditional Chinese medicine (TCM) obtained from TCM spectral detection. Through the motion detection, automatic selection of differential image and statistics of each spectral curve′s central-wavelength, the pixel points of TCM image are classified and the spectral image of TCM is divided into different areas automatically. Then spectral information is extracted from different areas of TCM′s spectral image and the effect of background noise on experimental result is eliminated obviously. As an example, images of Coptis chinensis and its mixed powder are processd with this arithmetic. The experimental results indicate that this arithmetic can automatically pick up effective areas in a precise way. It can better eliminate the interference from noises and would not produce any useless area.

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    Wang Lin, Hu Cuiying, Pang Qichang, Ma Ji, Cui Daijun. TCM Spectral Imaging Detection Based on Self-Adaptive Region Segmentation Method[J]. Laser & Optoelectronics Progress, 2013, 50(12): 121002

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    Paper Information

    Category: Image Processing

    Received: Aug. 20, 2013

    Accepted: --

    Published Online: Nov. 13, 2013

    The Author Email: Lin Wang (wlhgnc@163.com)

    DOI:10.3788/lop50.121002

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