玉米果穗粘连籽粒图像分割方法

为了对基于图像的玉米果穗穗粒数进行更精确的计算,给出了一种新的粘连籽粒图像分割方法。对粘连二值图像进行轮廓平滑和欧氏距离变换,将粘连籽粒的距离变换图视为地形学上的地形图,以地形图中的山谷线作为粘连二值图像的分割线。将欧氏距离变换图像的边界像素点视作水源点,根据山谷形态两边高、中间低的地形趋势设定水流的行进规则,使得水流在遇到山坡时自动绕行,但在遇到谷口点时可沿山谷线流动,从而将粘连籽粒分割开。该方法对单个未粘连籽粒不产生影响,不必在分割操作前依靠人工设定阈值进行籽粒是否粘连的判断,可以作为籽粒是否存在粘连的判断方法。用该方法对442个含不同粘连情况的籽粒连通分量进行判断与分割测试,粘连判断准确率为99.7%,粘连籽粒的分割准确率为94.9%。

Method of Image Segmentation for Touching Maize Kernels

With the aim to give a more accurate computing result of the maize kernel number based on image analysis, a new segmentation method for touching maize kernels was provided. First, contour smoothing and the Euclidean distance transformation were applied to the binary image of the touching kernels. Then the distance map was regarded as topographic relief and the valley lines were detected as the segmentation lines. Considering the boundary pixels of the distance map as water heads, the water will flow forward. They will turn when facing a slope and will go on when facing a valley mouth according to the terrain of the valley. This results in the segmentation. This method will take no influence on single kernels, so does not need a touching estimate by manual input threshold before segmentation. An experiment to 442 connected components of single kernels and multi touching kernels shows an accuracy of 99.7% for touching estimation and 94.9% for touching kernels segmentation.