Segmentation of leaf images using greedy algorithm

The Leaf is the important part of the plant which contains important information which will be playing a role in the identification and classification of plants. The identification of plants can be done with the help of image processing techniques. The techniques are used to understand, to analyze, to interpret and to get better quality of the images for human/machine perception. The image processing includes image pre-processing, segmentation, feature extraction and classification. In this paper, the leaf segmentation of different plant such as Jackfruit, Banaba, Cotton and etc. have been experimented using greedy snake algorithm and it is compared with the M Kass snake algorithm. From the comparison, it is observed that greedy algorithm is faster and efficient than the Kass algorithm in terms of iterations obligatory to get the desired contour of an image.