【摘要】 复杂背景叶片图像分割是当前的研究热点和难点。提出一种结合简单交互和标记分水岭的方法,有效地解决了该问题。首先,让用户在复杂背景叶片图像上奇偶相间地标定叶边缘点和叶外点;经过一系列处理得到标记图像。接着,把复杂背景叶片图像转换为灰度图像、L~*a~*b~*图像;以标记图像为参数,分别对灰度图像、a~*分量图像、b~*分量图像,进行标记分水岭分割。最后,以投票方式综合得到最终的分割结果。对20个种类,200张复杂背景叶片图像的分割实验表明:该方法能实现较准确的分割,并且能保留叶片细节部分;对个别叶片有细小的错分,但对其形状影响轻微。更多还原

【Abstract】 Segmenting leaf images with complex background is currently a difficult and focal point of research. In this paper,we propose a method which combines simple man-machine interaction with marker-based watershed segmentation to solve the problem of leaf image segmentation effectively. First,the method lets the user mark the peripheral and exterior points of a leaf in odd-even sequence on the leaf image under complex background; after a series of processing the marked image is produced. Secondly,the method transforms the leaf image under complex background into greyscale image and L~*a~*b~*image,then applies the marker-based watershed segmentation to greyscale image,a~*component image and b~*component image respectively with the previous marked image as parameters. Finally,the final segmentation result is achieved comprehensively by means of voting. The segmentation experiments on 200 leaf images in 20 categories under complex backgrounds indicate that this method can realise precise segmentation,and can preserve the detailed parts of a leaf. There are tiny mistakes in some segmentations,but have slight impact on leaf shapes.更多还原