A method for accurately segmenting images of medicinal plant leaves with complex backgrounds

The paper proposes a relatively accurate method of segmenting the leaf images of medicinal plants with complex backgrounds. The method directly takes photos of leaves on branches for the purpose of machine identification and protects the plant from leaf picking; but it also encounters higher difficulties in segmentation as branches, soil and other leaves appear inevitably in the background. On the basis of introducing user interaction when appropriate, we refer to and extend the OTSU concept to accurately detect adjacent outer points of the leaf corresponding to each manually marked edge point of the leaf. Afterwards, these points are selectively connected in a way that is close to but not going through the leaf edge as practically as possible so as to obtain background markers that are close to the leaf edge but correctly located outside the leaf. Last but not the least, by combining the foreground and background markers, we adopt the marker-based watershed segmentation method to obtain the correct segmentation result. As shown from test results based on the self-built database 1 consisting of 440 leaf images with complex backgrounds of 88 species of plants and the widely applied database 2 consisting of 232 leaf images with complex backgrounds, the method leads to a better result in five indexes like Precision and Recall, and is one upon the reported methods.