Abstract
Plant recognition and classification is required for the protection of biodiversity and for utilising them for human purposes. Not all people are having enough knowledge to recognize a plant while looking on to it. The developments in computer vision enhanced the use of computerized frameworks for recognition and classification of objects in surroundings. Plants can be classified based on their leaf pattern and other noval properties. Image recognition is closely related with neural networks which are developed to imitate that biological neural networks in human brain. Artificial neural networks are used to train with a large data set to recognize a new input data. The area of Artificial Intelligence is undergoing a drastic development and its use in computer vision made a huge impact. In this paper the history of plant recognition and features used for classification are analysed. Also various strategies for plant recognition using neural networks such as K-Nearest Neighbour(KNN), Support Vector Machine(SVM), Convolutional Neural Networks(CNN) are discussed.
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