Computer Vision –
Overview
Hanyang University
Jong-Il Park
Digital Image Processing
 Sampling & Quantization
 Image Enhancement
 Image Restoration
 Image Coding( or Image Data Compression)
 Image Understanding( or Computer Vision)
Department of Computer Science and Engineering, Hanyang University
Image formation
Department of Computer Science and Engineering, Hanyang University
Sampling & Quantization
Department of Computer Science and Engineering, Hanyang University
Department of Computer Science and Engineering, Hanyang University
Subsampling & aliasing
aliasing
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Sub-Nyquist sampling
Circular Zone Plate
Org.
H ½, v ½
aliasing
Department of Computer Science and Engineering, Hanyang University
Image Enhancement
 Goal
 to accentuate certain image features for subsequent
analysis or for image display
Input : image
Output : image
Department of Computer Science and Engineering, Hanyang University
Department of Computer Science and Engineering, Hanyang University
Department of Computer Science and Engineering, Hanyang University
Image Enhancement
 Techniques
 contrast/edge enhancement
 histogram equalization
 pseudo coloring
 noise filtering
 edge sharpening
 smoothing
 Applications
 processing of remote-sensed image via satellite
 radar, SAR, Ultrasonic image processing
Department of Computer Science and Engineering, Hanyang University
Image Restoration
 Goal
 to remove or minimize known/unknown degradations in
image
Department of Computer Science and Engineering, Hanyang University
Department of Computer Science and Engineering, Hanyang University
Blur model
n ( x, y )
g ( x, y )   h( x, y;  ,  ) f ( ,  )dd  n( x, y )
or g  Hf  n ; discrete model
 estimate or recover f(x,y) from g(x,y)
 deconvolution problem
Department of Computer Science and Engineering, Hanyang University
Enhancement by integration
Department of Computer Science and Engineering, Hanyang University
Image Restoration
 Techniques
 deblurring
 noise filtering
 correction of geometric distortion
 inverse filtering
 Least mean square(Wiener) filtering
 Applications
 remote-sensed image processing
 noise cancellation
Department of Computer Science and Engineering, Hanyang University
Image Data Compression
 Goal

to reduce the amount of data required to represent images
Input : image
Output : bit-stream data
“010100101100110101001 . . . .”
moving image:
7
1,0001,0008(bits/sample)330 frame/sec = 7210 bit/sec
Department of Computer Science and Engineering, Hanyang University
2-D Image Compression, JPEG
 Image quality by JPEG
(a) 27.9 dB at 0.125 bpp
(b) 31.5 dB at 0.25 bpp
(c) 34.8 dB at 0.5 bpp
Department of Computer Science and Engineering, Hanyang University
Department of Computer Science and Engineering, Hanyang University
Department of Computer Science and Engineering, Hanyang University
3D Mesh Compression
Model
Bunny
# of
Vertex
# of
Triangle
Original
(byte)
34835
69473
2,879,786
Compression ratio
Compressed (byte)
12 bpc
10 bpc
8 bpc
57,952
37,642
24,842
50 : 1
77 : 1
116 : 1
Original ‘Bunny’
12 bpc
10 bpc
8 bpc
Department of Computer Science and Engineering, Hanyang University
Image Data Compression
 Techniques
 Error-free coding( or lossless coding)
 Lossy compression
 Image Compression Standard
 JPEG, H.261, H.263, MPEG-1,2,4 etc
 Applications
 Transmission
 teleconferencing ,TV system, remote sensing via
satellite
 Storage
 VOD(video on demand), Video CD, DVD(digital video
disk), medical imaging, educational and business
documents
Department of Computer Science and Engineering, Hanyang University
Image Coding Standards
Standard
Application
Bit rate
JPEG
Still-image
Variable
H.261
Visual telephony and video conferencing
p64 kbps
H.263
< 64
kbps
MPEG-1
Full motion video on digital storage media 1.5 Mbps
MPEG-2
Higher resolution video than MPEG-1
 2 Mbps
HDTV
Terrestrial broad cast
 20 Mbps
Department of Computer Science and Engineering, Hanyang University
MPEG
 MPEG-1
 1992
 Video CD
 Includes Audio Layer III (MP3)
 MPEG-4
 Part 1: 1998
 Part 2: 1999 (addition still under development)
 Audio visual object
 Mobile telephony (IMT-2000)
 Interactivity
 Content –Based Interactivity
Department of Computer Science and Engineering, Hanyang University
 MPEG-7
 2001 (addition still under development)
 Content Description Interface
 Metadata language and schemes for search & retrieval
Department of Computer Science and Engineering, Hanyang University
Content-based Image Retrieval
 Image retrieval

Find similar images from
image database
 Used features

Color

Texture

Shape
Query
Retrieved
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Query
Image
Image
Data
List
Retrieval
Results
Texture
Option
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Content-based Video Retrieval
 Video retrieval
 Scene change detection and key frame extraction
 Extracted key frame from a movie clip
Department of Computer Science and Engineering, Hanyang University
Content-based Video Retrieval
 Video retrieval
 Automatic indexing
 Index from a news sequence
Department of Computer Science and Engineering, Hanyang University
Media Framework Tech.
 MPEG-21
 All electronic creation, delivery and trade of digital
multimedia content
 Transparent usage of various content types on various
devices connected through various network
Department of Computer Science and Engineering, Hanyang University
Watermarking

the process of embedding information into a host
signal without changing perceived characteristics
of the host
Key
Image/
Document
Watermark
Information
Watermark
Embedding
Key
* Filtering
* Lossy Compression
* Forgery
* Cropping & Scaling
* Geometric Distortion
Watermark
Detection
Decoded
Watermark
* Copy Protection
* Fingerprinting
* Authentification
Watermark
Generation
Department of Computer Science and Engineering, Hanyang University
Image Understanding
 Goal
 to interpret or describe the meaning contained in the
image
Input : image
Output : interpretation(description)
“KAISION”
“circle”
Department of Computer Science and Engineering, Hanyang University
Department of Computer Science and Engineering, Hanyang University
Department of Computer Science and Engineering, Hanyang University
Stereo Vision (disparity map)
기준 영상(좌)
기준 영상(우)
변위 참 값(붉은색: 가리워짐)
구한 변위 지도(검은색: 가리워짐)
Department of Computer Science and Engineering, Hanyang University
Scene Matching (1)
Model image
Model
Scene matching result
Input scene
Department of Computer Science and Engineering, Hanyang University
Scene Matching (2)
Model
Scene matching result
Input image
Edge image
Department of Computer Science and Engineering, Hanyang University
Fruit Classifier
 Apple

Orange
 Water Mellon
– 크기, 반지름
Department of Computer Science and Engineering, Hanyang University
– color
Department of Computer Science and Engineering, Hanyang University
Edge Detection
(a) Lena OriginalImage(256 256)
(b) CannyOperator(  2, low  5, high  10)
Department of Computer Science and Engineering, Hanyang University
Segmentation
(a) Aerial Original Image
(b) Segmented Image
Department of Computer Science and Engineering, Hanyang University
Department of Computer Science and Engineering, Hanyang University
 There are a lot of interesting topics to
explore in image processing and
computer vision.
Department of Computer Science and Engineering, Hanyang University