Leaf vein segmentation of medicinal plant using Hessian matrix

This paper proposes a leaf vein segmentation using Hessian matrix. Leaf venation pattern is a biometric feature that form the basis of leaf characterization and classification. It is specific in certain species thus it can be used as a key feature. Hessian Matrix is a method of the second derivative ridge detection that can be used to segment the image based on its group structure by analyzing eigenvalues of the pixel. We applied thinning to achive the better result of leaf vein. In addition, we performed morphological image processing to fix broken ridges or unconnected leaf veins. We have evaluated four veins type of 80 digital leaf. The experimental results show that 53.75% of leaf image scored 2 and 42.5% scored 1 which means our proposed method has good performance to extract the primary, secondary veins and tertiary leaf vein. This method is promising to help botanist and taxonomist identifying medicinal plant species automatically.