基于烤烟透射特征的烟叶图像分割研究

    Image segmentation based on transmission characteristics of flue-cured tobacco leaves

    • 摘要: 在专门设计的灯箱中拍摄烤烟烟叶的反射和透射图像,对这两类图像分别以3×3像素矩阵作为区域对象采样,统计比较了烟叶、背景两区域的RGB属性特征,发现透射图像烟叶区域绝大多数像素的蓝色属性等于零,少数像素的蓝色属性大于零,并在采样矩阵中呈不连续分布, 矩阵内9个像素蓝色属性的相对标准偏差(RSD)或等于零,或大于100%。研究采用该特征作为依据,对烟叶透射图像进行了区域统计法分割。结果表明分割精度高于点统计法,每片烟叶像素数平均高出0.65%,较好地保留了目标图像的原始特征信息。该研究提出的图像分割方法有利于提高分割结果的可信度,为利用烟叶透射特征进行后续研究奠定了基础。

       

      Abstract: Reflection and transmission images of flue-cured tobacco leaf were both taken in specially-designed lamp box, and then imported into computer for digital analysis. The comparison between the tobacco leaf area and background area for RGB attributes in these two types of images were conducted by sampling with a moving 3×3 matrix of pixels. It was found that most of the blue vector value of pixels in transmission image of tobacco leaf were equal to zero and few of them with greater than zero were distributed discontinuously within the matrix. It was also found that the relative standard deviation (RSD) of blue vector value in a matrix with nine pixels located on the tobacco leaf area in the transmission image was either 0 or more than 100%. Based on the findings, an approach to image segmentation with area-oriented statistics was thus proposed in this paper. The results show that the segmentation accuracy is higher than that by the method of point-oriented statistics, and the average pixels of all segmented image in this study were 0.65% more than those by point statistics per tobacco leaf. The characteristics of the original object image were well kept after segmentation. The presented method may be helpful to increase segmentation accuracy and lay foundations for further studies by using transmission characteristics of tobacco leaf.

       

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