Plant Recognition Based on Multi-Feature and Locality Preserving Projections Fusion Algorithm

Abstract

For the demand of leaf recognition under rotation condition. This paper propose a method to extract the multi-feature extraction and Locally Preserving Projection (LPP) fusion algorithm. First, the texture feature of the leaf is extracted by Local Binary Pattern (LBP) algorithm based on leaf block. Then, in order to improve the speed of feature classification recognition, this paper adopts LPP algorithm for feature dimension reduction of the high dimensional of LBP. In addition, combining leaf texture feature LBP with shape feature (Hu Moment invariants) after dimension reduction, shaping into the comprehensive characteristics of plant leaves. Finally, Support Vector Machine (SVM) classifier is used to establish classifier for classification and identification of plant leaves, the results of experiment have verified the validity of the algorithm in this paper.