International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
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Plant Leaf Recognition Using Machine Learning: A Review Dinesh Suresh Bhadane1, Suvarna Patil2, Abhay Bhandari3, Danish Mahajan4, Ajay Katoch5, Naman Abrol6 1,2 Assistant Professor, Dept. of Computer Engineering, Dr. D.Y. Patil Institute of Technology, Pimpri, Pune,
Maharashtra, India
3,4,5,6 B.E. student (Computer Engineering), Dr. D.Y. Patil Institute of Technology, Pimpri, Pune, Maharashtra, India
---------------------------------------------------------------------***--------------------------------------------------------------------provide important information about the species. Leaf Abstract - Plants classification through leaves is an
characteristics such as the shape, size, and colour, as well as the pattern of veins, hairs, or glands, can be used to differentiate between different plant species. The arrangement of leaves on the stem can also be used as a distinguishing feature. Moreover, leaves remain on the plants for most of the year, making them an ideal part to use for plant identification. Machine learning algorithms have become a popular method for plant identification. These algorithms can recognize patterns and features in plant leaves and use them to identify unknown plants accurately and quickly. Various machine learning algorithms have been used in the development of plant identification models, such as support vector machines, random forests, and deep neural networks. Additionally, image processing techniques have been used to extract features from plant leaves that can be used for plant identification. This paper reviews various studies conducted to develop plant identification systems based on leaf characteristics. The paper discusses the different machine learning algorithms used and the image processing techniques applied to extract features from plant leaves. The paper also explores the different applications of plant identification systems in agriculture and horticulture, such as weed detection, plant growth estimation, and disease detection. The development of plant identification systems has opened new opportunities in the identification of plants with medicinal properties. Plants have been used as medicines for centuries, and the identification of plants with medicinal properties can lead to the development of new drugs and treatments for various health disorders. The identification of plants with medicinal properties can be done through their leaves, and the use of plant identification systems can hasten the process. In conclusion, the development of plant identification systems based on leaf characteristics has numerous applications in agriculture, horticulture, and medicine. The identification of plants through their leaves has become more accessible, thanks to technology and the development of machine learning algorithms. The use of plant identification systems can help in the detection of plant diseases, weed control, and plant growth estimation, making it an essential tool in agriculture and horticulture. The identification of plants with medicinal properties can also be done through their leaves, leading to the development of new drugs and treatments for various health disorders. The paper aims to provide an overview of
innovating and fascinating area of research that can provide helpful information regarding plants. Plant identification using their leaves is important in agriculture for weed identification, plant growth assessment and classification of diseases in plants. In addition to this, leaves can prove to be an important factor in identification of plant species in comparison to other parts of plants including flowers, stems, and seeds. Although recent advancements in the field of machine learning have made leaf classification much easier. Identifying plant species using their leaf images proves to be a challenge due to the vast variation among species and variations in their shape, size, and color. This review paper gives a detailed literature review of numerous tools and algorithms used in plant classification, providing their potential results and high accuracy. Some of the most commonly used leaf classification methods include support vector machines, convolutional neural networks, and decision trees. These algorithms have many applications, including estimating carbon uptake, predicting yields, and monitoring plant health and biodiversity. Plant classification through leaves can have applications in various area of interest such as agriculture, botanical research, medicine (Ayurveda) etc. In Ayurveda, plants are used as medicines providing solutions to diabetes, digestive problems, diseases related to the heart, liver disorder, etc. As machine learning and image recognition evolve, plant classification will have an even more significant impact in these fields.
Key Words: Machine Learning, Deep Learning, Plant Recognition, Pre-processing, Feature Extraction
1. INTRODUCTION Plants play a crucial role in the ecosystem and have been used for various purposes throughout history. From agriculture to medicine, plants have been a source of sustenance and healing for humans. Identifying plants is important in agriculture for weed detection, plant growth estimation, and disease detection. Manual identification of plants through their leaves is a time-consuming and tedious job, which can be counteracted by the development of a plant identification system. In recent years, technology has made plant identification more accessible, and various plant identification systems have been developed. Leaves are the most important part of a plant for classification as they
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