基于自适应双阈值的彩色线阵CCD小麦黑胚分割

    Color linear CCD black germ segmentation of wheat kernel based on self-adapting dual threshold

    • 摘要: 在粮食质量等级评定中,黑胚粒存在的多少影响小麦的整体等级划分。该文以产自新疆和河南不同品种的710粒有黑胚的小麦、627粒破损小麦和1 167粒正常小麦为研究对象,采用彩色线阵CCD动态获取小麦图像,对原始图像进行多余背景去除、色偏校正、亮度变换以及形态学处理后,再对小麦图像单通道图像进行自适应双阈值分割,能有效的实现对小麦黑胚特征的分割。试验选择三种小麦进行特征提取以及模式识别,得到最佳分辨率分别为95.1%,96.0%和98.3%。结果表明该方法对小麦黑胚的识别具有良好的效果。

       

      Abstract: In the assessment of food quality grade, the number of black germ kernels will affect the overall classification of wheat. With 710 wheat kernels containing black germ kernels, 627 break kernels and 1 167 normal wheat kernels produced in Xinjiang and Henan province,the color linear CCD was used to acquire images of the wheat kernels. After removing the margin of original image background, correcting color offset, image enhancing, morphological processing and ternary of the original image, the feature of black germ kernels was extracted effectively. In the experiment, the recognition accuracy of black germ kernel, break kernel and normal kernel were 95.1%, 96.0% and 98.3%, respectively. The results show that the method is feasible and effective to segment black germ kernels.

       

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