An Overview of the Research on Texture Based Plant Leaf Classification
Vishakha Metre, Jayshree Ghorpade

TL;DR
This paper reviews various texture-based methods for plant leaf classification, emphasizing their importance in agriculture and biology, and compares their performance to identify the most effective techniques.
Contribution
It provides a comprehensive overview of texture-based plant leaf classification methods and evaluates their effectiveness to determine the best performing approach.
Findings
Texture-based methods are effective for plant leaf classification.
Some methods outperform others in accuracy and efficiency.
The paper identifies the most efficient classification technique.
Abstract
Plant classification has a broad application prospective in agriculture and medicine, and is especially significant to the biology diversity research. As plants are vitally important for environmental protection, it is more important to identify and classify them accurately. Plant leaf classification is a technique where leaf is classified based on its different morphological features. The goal of this paper is to provide an overview of different aspects of texture based plant leaf classification and related things. At last we will be concluding about the efficient method i.e. the method that gives better performance compared to the other methods.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSmart Agriculture and AI · Leaf Properties and Growth Measurement · Spectroscopy and Chemometric Analyses
