A Review on Identification of Plant Leaf Image Classification Using Machine Learning Algorithms

Abstract

Generally, plants possess great medical benefits that are tremendously diverse and complex to identify the species. There are different varieties of plants that are yet to be fully explored. The plants are made up of some essential parts that are needed for their survival, such as roots, flowers, leaves, shoots, and others, which often appear to be alike with each other. This makes manual sorting of plants more difficult for botanists. Concurrently, image processing performs some operations by extracting useful information from the image for human interpretation. The resulting dataset from the image processing method is then classified by ML (Machine Learning) classifiers. The existing methods have focused on several dimensions; this study provides an overall view of the conventional works of plant species identification and its related plant health. This study was initiated with the purpose of giving a precise review of the advancements in image processing, such as segmentation methods, feature extraction techniques and ML-based models for the identification of plant species and diseases with its leaf because that can be available at all times. Hence, this study discusses the current research between (2019–2024) related to the use of image processing and ML and DL techniques for effective image quality enhancement and plant identification performance. Moreover, it discusses unique contributions in the field, such as agriculture and ayurveda. Moreover, a comparative analysis is carried out by considering the conventional ML models and the varied applications of widely used ML models for the effective classification of plant species.

Plant phenotyping relevance

葉画像のセグメンテーション、特徴抽出、機械学習・深層学習による植物病害の画像分類を対象とする方法レビューであり、植物の病態推定手法が中心です。種同定も含みますが、病害・植物健康の画像解析手法を体系的に扱っているため採用します。

Code and data availability

公開本文の所在を確認できませんでした。非公開または購読が必要な可能性があります。

No evidence-backed public reproduction asset is currently recorded.