Download - Conference e04 1
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Digital Image Processing pproach for Fruitand Flower Leaf Identification and
ecognition
Submitted by,Rahul H .N.
4JN11IS421
Guided by,
M r. Pavan Kumar M .PLecturer, Dept. of I nformation Science & Eng.
JNNCE, Shimoga
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CONTENTS
Introduction
System design
Techniques
Extraction features
Recognition & its method
Conclusion
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INTRODUCTION
Digital Image processing technique
Pattern recognition
Categorize of image processing
Applications
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INTRODUCTION.
It is difficult to analyze the plant
based on 2D & 3D images .
We can t define the the plant based
on the leaf color or based on the
fruit all the time.
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Sys tem Design
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IMAGE PROCESSING ALGORITHM
Yes
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LEAF FEATURE EXTRACTION
Basic quantity descriptors Area (A) Perimeter (P)
Maximum length (L) Maximum width (W) Convex hull (H)
Dimensionless shape factors Compactness (C)
Roundness (R) Elongation (E) Roughness (G)
Conventional Morphological Features
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LEAF FEATURE EXTRACTIONFourier descriptors
Steps to extract Fourier descriptors
Find the major axis of seedling leaf
with Hotelling transform
Rotate seedling leaf to horizontal position
and select 256 points on the leaf boundary
Convert x-y coordinates of boundary points
to complex number
Use FFT algorithm to obtain
Fourier transform coefficient
Normalization of Fourier transform
coefficients to obtain Fourier descriptors
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LEAF FEATURE EXTRACTIONFourier descriptors
Original Image Binary Image
N=256 N=128 N=64 N=32
N=16 N=8 N=4 N=2
Cabbage
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LEAF FEATURE EXTRACTIONFourier descriptors
Original Image Binary Image
N=256 N=128 N=64 N=32
N=16 N=8 N=4 N=2
Lettuce
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LEAF FEATURE EXTRACTIONBezier descriptors
Steps to obtain Bezier descriptors
Image acquisition Image segmentation Boundary detection
Finding leaf tip and
leaf base
Fitting boundary with
Bezier curves
Normalization and
obtain bezier descriptors
A B C
D E F
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LEAF FEATURE EXTRACTIONBezier descriptors
Bezier descriptors Leaf tip angle Leaf base angle Left control line ratio Right control line ratio Normalized controlpoint coordinates
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RESULTS
Leaf features at different growth stages
Basic morphologic features
Bezier descriptors
Applications
Geometric Modeling of Seedling Leaves
Leaf Shape Comparisons and Plant
Identification
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APPLICATIONSGeometric Modeling of Seedling Leaves
Wire Frame Model Perspective View Mapping with Texture
Elliptical Model
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Top View
Side View
Real Image Graphics Simulation
APPLICATIONS3D Reconstruction of Seedling Structure
Graphic Simulation of Cabbage Seedling
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APPLICATIONS
Leaf Shape Comparisons and Plant Identification
Leaf
Feature
Extraction
Leaf Image
Morphological
Features
Fourier
Descriptors
Bezier
Features
PatternRecognition
Statistical Analysis
Neural Network
Cluster Analysis
Genetic Algorithm
Plant
Identification Applications
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CONCLUSIONS
The recogni tion of local f rui t trees through leaf
structures using image processing techniques.
Chain code method is a method that was used to
obtain the shape of an object.
I n addition, a linear feature recogni tion technique
for comparison was successful implemented to
achieve the objectives of the research.
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Digital image processing- fruit tree
category, provide its statistical analysis and
general information using an image of aleaf as a parameter.
CONCLUSIONS
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THANK YOU