• Jignesh B. Jethva
• Dr. C. R. Singla

This paper presents a classification approach by Random Forest Classifier algorithm for classifying the different types of plants. This Proposed Approach consists of four phases that are image pre-processing, feature extraction, features fusion and classification phases. Most types of plants have unique leaves. There are many features of leaf such as Color features, Vein features, GLCM features, Shape features and Gabor features. Also calculate Zernike moments such as amplitudes and phase. These all features are fused by concatenating of two vectors. So classification approach presented in this research depends on plant’s leaves. Experimental results show accuracy and other parameters measured in this approach with fusion of all these features or their different combinations.

Random Forest, Zernike Moment, Gabor Filters, GLCM.

"Leaf Classification by Random Forest Classifier Based On Leaf Features Fusion & Zernike Moment", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.13-19, August-2018, Available :http://www.jetir.org/papers/JETIRD006003.pdf

"Leaf Classification by Random Forest Classifier Based On Leaf Features Fusion & Zernike Moment", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp13-19, August-2018, Available at : http://www.jetir.org/papers/JETIRD006003.pdf