中药光谱成像图像自适应区域增长分割方法

张万祥, 庞其昌, 赵静, 林富斌

张万祥, 庞其昌, 赵静, 林富斌. 中药光谱成像图像自适应区域增长分割方法[J]. 应用光学, 2010, 31(1): 78-82.
引用本文: 张万祥, 庞其昌, 赵静, 林富斌. 中药光谱成像图像自适应区域增长分割方法[J]. 应用光学, 2010, 31(1): 78-82.
shu
ZHANG Wan-xiang, PANG Qi-chang, ZHAO Jing, LIN Fu-bin. Self-adaptive region growing algorithm to segment images of spectral imaging for TCM assessment[J]. Journal of Applied Optics, 2010, 31(1): 78-82.
Citation: ZHANG Wan-xiang, PANG Qi-chang, ZHAO Jing, LIN Fu-bin. Self-adaptive region growing algorithm to segment images of spectral imaging for TCM assessment[J]. Journal of Applied Optics, 2010, 31(1): 78-82.
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中药光谱成像图像自适应区域增长分割方法

  • 1.

    暨南大学广东省高等学校光电信息与传感技术重点实验室,广东广州510632;

  • 2.

    华南农业大学应用物理系,广东广州510640

详细信息
    通讯作者:

    张万祥(1985-)，男(彝族)，云南玉溪人，硕士研究生，主要从事光谱成像重要检测技术数据处理方法研究。

  • 中图分类号: TN911.73；R282.5

Self-adaptive region growing algorithm to segment images of spectral imaging for TCM assessment

  • 1.

    Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Educational Institutes,Jinan University,Guangzhou 510632,China;

  • 2.

    Department of Applied Physics,South China Agricultural University,Guangzhou 510640,China

摘要

    摘要
  • 摘要: 为了消除背景噪声对药材光谱图像检测结果的干扰，根据中药材光谱图像的特点，设计一种能够自适应对中药材光谱图像进行有效区域(ROI)分割的区域增长算法。该区域增长算法根据药材光谱图像的灰度直方图分布来自动选取种子点和分割阈值，在生长的同时进行连通性分析，生长结束后通过区域填充技术来消除图像中出现的孔洞。实验表明：该方法能够自动、准确地进行ROI分割，分割偏差小于8%，并且能较好地消除噪声的干扰，没有产生无意义的生长区域。
    Abstract: The spectral imaging method for assessing the traditional Chinese medicine (TCM) can evaluate the quality of the medicines and identify their authenticity by using their spectral images. It can also make the assessing procedure fast and non-destructive. In order to eliminate the influence of the background noise on the assessing results of TCM spectral images, extraction of ROI (region of interest) of the TCM spectral images is needed. Since the difference inherent in different kinds of TCM spectral images and the available fixedthreshold segmentation method can not meet the demand of selfadaptive segment, a self-adaptive region growing algorithm to extract ROI of the images is proposed based on the characteristic of TCM. This algorithm can automatically choose the seeds and threshold of the region growing process according to the gray-level histograms of the TCM spectral images, the connectivity among the pixels is taken into the consideration during the growing period, and the region-fill technique is applied to modify the cavity in ROI after the growing. It proves that this algorithm can extract ROI of the images automatically and precisely, the deviation of segmentation is less than 8%, its antinoise ability is good, and the nonsensical growing result is not appear.
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    • 参考文献(1)
  • ［1］孙素琴,周群,郁鉴源,等.分子振动光谱法与中药研究的最新进展［J］. 光谱学与光谱分析，2000(02)：199-202.
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    ［7］舒添慧, 胥布工，胡战虎. 基于区域生长法的医学图像分割［J］. 微计算机信息,2008(6):284-285.
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  • 刊出日期:  2010-01-14

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