Application Research of Multi-Feature and Locally Linear Embedding Fusion Algorithm in Plant Recognition

For the demand of leaf recognition under rotation condition, the plant multi-feature extraction and local embedding fusion algorithm was applied to classify plant leaves by Support Vector Machine (SVM).Results showed that the texture feature of the leaf was extracted by Local Binary Pattern (LBP) algorithm based on leaf block.Using Locally Linear Embedding (LLE) algorithm, dimensionality reduction of high dimensional LBP features reduced the classification and recognition time, and at the same time could achieve better clustering effect and effectively improved the recognition rate.The proposed method for identifying plant leaves had good utility for the leaves in the rotated state.