In this paper, particular attention is paid to the implementation of machine learning techniques for leaf classification. Our goal is to demonstrate how machine learning algorithms can be used to analyze a series of leaf photographs to achieve accurate classification and provide algorithms that are valuable to the botanical field.
The Nature of Machine Learning in Image Processing
Machine learning has revolutionized the field of image processing by enabling computers to learn patterns and make predictions based on visual data. In the context of leaf classification, machine learning algorithms can be trained on datasets of labeled leaf images to identify and classify different species based on their unique characteristics. By harnessing the power of machine learning, we can automate the leaf identification process and contribute to plant research and conservation efforts.
First, let's import all required libraries.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from math import isclose
from fractions import Fraction
from skimage import data, io, filters, util, color
from skimage.morphology import (disk, square, rectangle, skeletonize,