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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 14, ISSUE 5, MAY 2025

AN OVERVIEW ON: Plant Identification through Leaf Image

Prof. Pranita Chandankhede, Prathamesh Nagore, Ashish Chaudhari, Vaishnavi Golit, Yogesh Rakhunde, Gaurav Gajbhiya

DOI: 10.17148/IJARCCE.2025.14562

Abstract: This paper presents an intelligent system for plant identification through the analysis of leaf images, utilizing image processing and machine learning techniques. The model extracts key leaf features such as shape, color, texture, and vein patterns to classify plant species accurately. This approach provides an accessible, efficient, and scalable method for botanical studies, conservation efforts, and educational purposes. The system emphasizes ease of use, requiring only a smartphone or basic imaging device. By leveraging convolutional neural networks (CNNs) for classification, the proposed model achieves high accuracy in species recognition. This paper explores the system's design, methodology, experimental evaluation, and future applications.

Keywords: Plant Identification, Image Processing, Leaf Recognition, Machine Learning, Convolutional Neural Networks (CNN).

How to Cite:

[1] Prof. Pranita Chandankhede, Prathamesh Nagore, Ashish Chaudhari, Vaishnavi Golit, Yogesh Rakhunde, Gaurav Gajbhiya, β€œAN OVERVIEW ON: Plant Identification through Leaf Image,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.14562