LEAF RECOGNITION ALGORITHM FOR PLANT CLASSIFICATION USING K-MEANS SEGMENTATION AND NEURAL NETWORK
In this project, Probabilistic Neural Network (PNN) and K-Means Segmentation with image and data processing techniques to implement a general-purpose automated leaf recognition. Twenty leaf features are extracted and orthogonalized into 5 principal variables which consist of the input vector of the PNN. The PNN is trained with K-Means Segmentation to classify the plants with an accuracy greater compared with other approaches.
Reference Paper: A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network
Author’s Name: Stephen Gang Wu, Forrest Sheng Bao, Eric You Xu, Yu-Xuan Wang, Yi-Fan Chang, and Qiao-Liang Xiang
Source: IEEE
Year:2007
Request source code for academic purpose, fill REQUEST FORM or contact +91 7904568456 by WhatsApp or info@verilogcourseteam.com, fee applicable.
SIMULATION VIDEO DEMO
