利用自适应图像分割算法处理中药光谱检测中得到的中药光谱图像，通过运动检测、差分图像的自动选取及光谱曲线中心波长统计对中药图像的像素点进行分类，将中药光谱图像自动分割成不同的区域，提取中药材光谱图像不同区域的光谱信息并消除背景噪声对实验结果的影响。以中药黄连及其混合粉末为例进行实验。实验结果表明该算法能够自动准确地提取出有效区域，并分割出有效区域的光谱图像，较好地消除了噪声干扰并且没有产生无意义的区域。

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.