Template based Shape Feature Selection for Plant Leaf Classification

Chaki, Jyotismita

doi:10.21817/ijet/2017/v9i3/1709030122

Cited by 4 publications

References 5 publications

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Segmentation and Features Extraction of Malaysian Herbs Leaves

Halim

Afrouzi

Lazim

2021

J. Phys.: Conf. Ser.

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In modern medical practice, herbs play a very important role as the source of bio-technology. Therefore, providing a database containing information of these herbs is significant to assist the medicinal practitioners and users. Image recognition, a process that includes image segmentation, features extraction and classification, is one of the methods to develop the database for herbs. This paper focuses on image segmentation and features extraction of 125 images with 1616×1080 pixels of Malaysian Herb Leaves including Sirih, Mexican Mint, Rerama, Belalai Gajah and Senduduk. The images were first segmented using Sobel operator to get the boundary points. Then, 7 geometrical features and 7 textural features were extracted for each image including area, perimeter, major axis length, minor axis length, roundness, smoothness and flatness. The experimental results were obtained using MATLAB R2018a. The results show that Sobel can successfully segment the images and calculates the features of the herb leaves.

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Segmentation and Features Extraction of Malaysian Herbs Leaves

Halim

Afrouzi

Lazim

2021

J. Phys.: Conf. Ser.

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Plant species identification using leaf biometrics and swarm optimization: A hybrid PSO, GWO, SVM model

Eid

Abraham

2018

HIS

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Machine Learning and Convolution Neural Network Approaches to Plant Leaf Recognition

Rajesh

2022

Research Anthology on Ecosystem Conservation and Preserving Biodiversity

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Plants are very important for the existence of human life. The total number of plant species is nearing 400 thousand as of date. With such a huge number of plant species, there is a need for intelligent systems for plant species recognition. The leaf is one of the most important and prominent parts of a plant and is available throughout the year. Leaf plays a major role in the identification of plants. Plant leaf recognition (PLR) is the process of automatically recognizing the plant species based on the image of the plant leaf. Many researchers have worked in this area of PLR using image processing, feature extraction, machine learning, and convolution neural network techniques. As a part of this chapter, the authors review several such latest methods of PLR and present the work done by various authors in the past five years in this area. The authors propose a generalized architecture for PLR based on this study and describe the major steps in PLR in detail. The authors then present a brief summary of the work that they are doing in this area of PLR for Ayurvedic plants.

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Template based Shape Feature Selection for Plant Leaf Classification

Cited by 4 publications

References 5 publications

Segmentation and Features Extraction of Malaysian Herbs Leaves

Segmentation and Features Extraction of Malaysian Herbs Leaves

Plant species identification using leaf biometrics and swarm optimization: A hybrid PSO, GWO, SVM model

Machine Learning and Convolution Neural Network Approaches to Plant Leaf Recognition

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