Abstract

Complete environment system depends on various plants. Plants help to maintain ecological system by controlling\npollution and providing oxygen etc. but due to inappropriate information about plant may lead to decreasing the number of\nplant species resulting in imbalance in ecological system. Hence an automated system is required for botanists to categorize\nplants for maintains the database for further researches. In this field, computer vision techniques have proven significant\ntechniques. For plant classification, an automated system is presented using improved pre-processing (by improving image\nenhancement or filtering scheme). Furthermore, wavelet feature and local features are also combine for feature vector\nformulation. Finally, a comparative classification study is presented where KNN, Neural Network and SVM classifiers are\nimplemented. experimental study shows that SVM provides better classification performance and further performance can be\nimproved by using combined feature extraction model.