CS462 Image Processing

จาก Paween Khoenkaw

Welcome to Image Processing class !!


Facebook page:https://www.facebook.com/groups/1419810698112412/

Course description

Introduction to digital image processing; Human visual system and visual psychophysics; Image acquisition; Sampling and quantization; Digital images structure; Digital images formats; Digital images characteristic Noise and noise filters; Degradation model; Noise models; Restoration; Image segmentation


Week
Lecture
Lab
1
Introduction

-Image processing and related science

-Human visual perception

-Introduction to Matlab

-Matlab programming basic

2
Image Acquisition

-Spatial Cartesian coordinate

-Camera model

-Sampling and Quantization

-Bitmap Image representation

-Color representation

-Read image file

-Matrix manipulation

-Display image

-Resize image

-Color plane separation

3-4
Image Characteristic

-Luminance

-Brightness, Contrast

-Pixel distance measurement

-Histogram

-Normalization and Equalization

-Image luminance manipulation

-Image matching

5
Image Filter

-Thresholding

-Convolution

-Smooth image

-Sharpen image

-Edge detection algorithm

-Image cleaning and sharpening

-Image effect

6-7
Image segmentation

-Neighborhood

-Erosion, Dilation

-Watershed

-Active contour

-False color image

-Counting object in image

-Optical character recognition (OCR)

Midterm Exam
8
Color Processing

-Color spaces

-RGB

-Indexed color

-HSV,YUV

-Color object detection

-Color manipulation

-Chroma Key (blue screen)

9
Image compression

-Channel Sub-sampling

-Run length encoding (GIF)

-Chain Code

-Discreet cosine transform

-JPEG Compression Algorithm

-Image compression

-Image smoothing

10
Image restoration

-Noise model

-Restoration

-Geometry transformation

-Camera calibration

-Image cleaning

-Restoration



11-13
Image recognition technic

Object detection (face/shape)

Hought Line Transform (line detection)

Hought Circle Transform (circle detection)

-Detect various shape in image
14-15
Motion

-Principle of Video

-Video camera

-Motion detection (BG model)

-Motion Estimation (MPEG)

-Optical flow

-Webcam

-Surveillance camera application



Final Exam

Slides

  • Slide will be available shortly after class!

Course Outline

1 Introduction and Image Acquisition

2 Image Characteristic I

3 Image Characteristic II

4 Image Filter

5 Image Segmentation and Labelling

6 Color Processing

7 Discrete Cosine Transform and JPEG Compression

8 Basic OCR

Lab Sheet

Lab 1 Image and Matrix

Lab 2 Exposure Manipulation

Lab 3 Image Similarity

Lab 4 Image Filter

Lab 5 Image Segmentation and Labelling

Lab 6 Color Processing

Lab 7 Discrete Cosine Transform and JPEG Image Compression

Resources

Download OpenCV 3.0 for Windows, (For Mac or Linux)

Python2.7(64bit)+OpenCV3.1

bitmap.txt

small.jpg

lena512color.tiff

frontier_color57.jpg

histogram_dataset.zip

image_dataset1.zip

template.mat

Unequalized_Hawkes_Bay_NZ.jpg

match2_1.tiff

match2_2.tiff

image1.mat

hilow.png

noise1.bmp

noise2.bmp

noise3.bmp

Pavlovsk_Railing_of_bridge_Yellow_palace_Winter.jpg

Valve_original_.PNG

letter.bmp

Plasma.jpg

otsu1.jpg

otsu2.jpg

crack.jpg

coins.jpg

cameraman.tif

solarwind.bmp

tomato.jpg

orange.jpg

led.jpg

highway.jpg

cloud.jpg

cat.jpg

JPEG Quantization tables

lab7_2.mat

jpeg_image.mat

jpeg_image2.mat (512 x 512 pixel)


faces2.jpg

faces.zip

haarcascade_frontalface_alt.xml

subject02.happy.png

javacv_core.zip

face_demo.txt

Java OCR Example code

Python OCR

OCR Test Image

[Java Image Descriptor code]

Source code

Otsu normal method

Otsu faster method

Javacode for imshow function

Zigzag function for entropy encoding

Inverse function for zigzag

Run length encoding function