Research On Leaves Recognition Based On Fractal Dimension

Our country owns a large number of plant species and is rich in forest. As environment problem rises, the number of endangered plant is increasing greatly. And the low efficiency and high subjectivity of manual recognition are great defect to plant recognition. Because of all of these, the study of plant recognition technique which is based on computer has important significance. Leaf is an essential part of plant. Different plant has leaves with different shape and texture features, according to these features we can recognize plant species with high accuracy.In this paper, the knowledge of fractal theory is introduced firstly, including the definition and different measure method of fractal and how the fractal can be used as texture feature. Next the technique which is necessary in image recognition is presented, such as feature extraction, principal component analysis and so on. And then the method of leaves recognition based on fractal dimension is implemented.21-dimensional shape and texture features is chosen after image pre-process and select the top 10 principal component to represent leaf image. Then SVM classifier is used to classify the leaves images. Finally, the experiment tested on 390 images which belong to 26 kinds of leaves. The result of experiment proves that fractal dimension which is used as texture feature can increase recognition accuracy. This method provides new way to certain utility value.