Lecture 11 Image processing technique 2.pdf

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Image processing #2

고급건설재료학

서울대 건설환경공학부 문주혁 교수

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Contexts

• #1. Introduction and Examples

• #2. Basics of Matlab, Image Processing Toolbox

• #3. Segmentation, Edge detection, Transformation

• Matlab code (Image processing toolbox)

• Project introduction

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Basics of Matlab

• Numeric types

• Signed integer:

• int8, int16, int32, int64

• Unsigned integer:

• uint8, uint16, uint32, uint64

• Floating point:

• single, double

• Other types

• Logical:

• True, false (1,0)

• Character:

s = ‘this is a string’

• Variables can be cast to different types:

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Basics of Matlab

Arrays Order (allocating memory)

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Basics of Matlab

• Arrays

Data Structures in Matlab

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Basics of Matlab

Data Structures in Matlab

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Basics of Matlab

Pre-Allocation

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Image Processing Toolbox

Image read and show

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Image Processing Toolbox

Image transformation to black-white (binary) image

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Image Processing Toolbox

Image processing

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Image Processing Toolbox

Image processing

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Image Processing Toolbox

Image processing

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Image Processing Toolbox

Image processing

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Image Processing Toolbox

Image processing

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Image Processing Toolbox

Image processing

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Image Processing Toolbox

Image processing

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Image Processing Toolbox

• Region Properties!!!

Start it over

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Image Processing Toolbox

Region Properties!!!

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Image Processing Toolbox

Region Properties!!! (Use Help! Regionprops)

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Image Processing Toolbox

• Image types

• True color (RGB, CMYK etc)

• Grayscale (or gray level, intensity) Binary (black & white, bi-level)

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Image Processing Toolbox

• Image types

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Image Processing Toolbox

• Image types

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Image Processing Toolbox

• Ok. Then what is the principle for im2bw? (RGB to Gray to Black & White)

Threshold value를 k라 하자.

[1, 2, … , 𝑘]를 가지는 픽셀들의 집합𝐶₀ 𝑘 + 1, 2, … , 𝐿 을 가지는 픽셀들의 집합𝐶₁ 𝐶₀에 속할 확률𝑤₀= 𝑤(𝑘)

𝐶₁에 속할 확률𝑤₁= 1 − 𝑤(𝑘) 𝐶₀의 평균값𝜇₀ = 𝜇(𝑘)/𝑤(𝑘) 𝐶₁의 평균값𝜇₁=^𝜇^𝑇^{−𝜇(𝑘)}

1−𝑤(𝑘)

Original 1 threshold

3 thresholds 2 thresholds

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Project

#1 Particle size analysis of 2D SEM image of superabsorbent polymers

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Project

#2 Particle size analysis of 2D SEM image of silica fume

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Project

#3 3D pore characteristics analysis of pores in concrete

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Project

#4 3D volumetric characteristics analysis of steel fibers in Ultra-High Performance Fiber-Reinforced Concrete (UHPRFC)

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Project

#5 Noise cancellation in video

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Project

#6 2D or 3D fiber separation in UHPFRC

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Project

#7 Fourier Transformation of TEM image

Lattice images of nanocrystalline regions in C-S-H in OPC specimen 28 d old

C-S-H particle