基于逐步改变阈值方法的玉米种子图像分割

    Separation of corn seeds images based on threshold changed gradually

    • 摘要: 针对图像处理中玉米计数的问题,提出了基于逐步改变阈值的分水岭变换方法。首先,对二值图像进行欧氏距离变换,合并图像中灰度值大于或者等于初始阈值的区域,并通过分水岭算法初步分割图像。为避免单粒玉米被过度分割,提取图像中单个种子区域存入结果图像。然后,判断去除单粒玉米后的图像是否为空;如果不为空,增大分割阈值并重复上述操作。最后,统计目标图像中的玉米个数。对50幅种子数目500粒左右的图像进行处理,分割正确率为97.7%,较好地解决了粘连玉米的分割问题。该方法已成功应用于基于机器视觉的玉米计数。

       

      Abstract: The watershed transform with gradually changing threshold was proposed for image segmentation of corn count using image processing method. First, binary image was processed with Euclidean distance transform, and regions which values higher than the initial threshold in this image were merged, then the image was segmented by watershed transform. To avoid over-segmentation, single seed regions were cut from source image and pasted in the result image. After that if source image was not empty, was threshold increaseed and the above process was repeated. Finally, the corn seeds amount of the result image was counted. In this paper, 50 images with about 500 corn seeds were tested. The correction rate of segmentation was 97.7%. The method can resolve the problem of separating touching corn effectively and is applicable in corn kernels counting.

       

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