Comparative study of various classification algorithms combined with K means algorithm for Leaf Identification

Plants play a vital role in our daily life. Plants are a great source of medicine for many diseases. Due to their fewer chances of side effects on human body and also better compatibility with humans, using plant for treating diseases is considered to be safer. Other items like paper, bio-diesel are also obtained by using plant material. Hence identification of plants is a very important task helpful for various areas such as Agriculture, Ayurveda, Botanical research, Biological research, etc. Leaf based features can be used for appropriate results than other parts of the plant in the plant identification. Manual leaf identification is very difficult and time consuming task. To implement automatic leaf identification, classification techniques like Naïve Bayes classification, Neural Network, etc can be used. To get the leaf based features, image processing techniques are applied on the image of leaf. After leaf based feature extraction, a plant’s leaf is classified based on the leaf features. The main objective of this paper is to present a survey of different classification methods for plant leaf identification. At the end, this paper concludes better classification method with more accuracy when compared to other classification methods. Keywords— Plant leaf identification, Classification, Leaf based features, Image processing.