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Image Processing Ch1: Introduction Prepared by: Hanan Hardan Hanan Hardan 1
Image Processing
Ch1: Introduction
Prepared by: Hanan Hardan
Hanan Hardan 1
Introduction
“One picture is worth more than ten thousand words”
Hanan Hardan 2
References
“Digital Image Processing”, Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2002
Much of the material that follows is taken from this book
“Machine Vision: Automated Visual Inspection and Robot Vision”, David Vernon, Prentice Hall, 1991
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Contents
This lecture will cover:
What is a digital image?
What is digital image processing?
State of the art examples of digital image processing
Key stages in digital image processing
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What is a Digital Image?
A digital image: is a representation of a two-dimensional image as a finite number of elements, each one has a particular location and value.. These element are called picture elements, image elements or pixels.
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What is a Digital Image? (cont…)
Pixels: Elements of the digital image , each has intensity.
Intensity of pixel: the amplitude غزارة of
gray level (in gray scale images)
1 pixel
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What is digital Image?
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What is digital Image?
An image can be defined as function of 2 variables , f(x,y), where x and y are spatial coordinates, and the amplitude of f at any pair of coordinates (x , y) is called the intensity of the image at that point
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What is digital image?
The image consists of finite number of pixels ( f(x,y) )
Every pixel Is an intersection between a row and a column.
Every pixel has intensity
pixel
Ex:
f(2,6)= 123
Refers to a pixel existing on the intersection between row 2 with column 6, and its intensity is 123.
Remember digitization implies that a digital image is an approximation of a real scene
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Digital image processing focuses on two major tasks
Improve image quality(pictorial information) for human perception and interpretation
Processing of image data for storage, transmission and representation for autonomous machine perception
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1. Computer Graphics: the creation of image
2. Image processing: enhancement or other manipulation of the image
3. Computer vision: analysis of the content
Image processing fields:
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What are digital image processing levels?
low level processes:
Input and output are images
Tasks: Primitive operations, such as, image processing to reduce noise, contrast enhancement and image sharpening
مثال صورة قديمة نريد تحسينها
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What are digital image processing levels?
Mid-Level Processes:
Inputs, generally, are images. Outputs are attributes extracted from those images (edges, contours, identity of individual objects)
Tasks:
Segmentation (partitioning an image into regions or objects)
Description of those objects to reduce them to a form suitable for computer processing
Classifications (recognition) of objects
صورة لكرسي نريد تعديلها حاسوبيا لنبرز حوافه : مثالHanan Hardan 13
What are digital image processing levels?
High-Level Processes
Input: Attributes Output: Understanding
Tasks: recognizing objects
Image analysis and computer vision(Analysis of the image content)
Examples: Scene understanding
صورة لمشتبه فيه نريد الحاسوب ان يتعرف عليه: مثال
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Uses of DIP
Image enhancement/restoration
Artistic effects
Medical visualisation
Law enforcement
Human computer interfaces
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Examples: Image Enhancement
One of the most common uses of DIP techniques: improve quality, remove noise etc
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Examples: The Hubble Telescope Launched in 1990 the Hubble telescope can take images of very distant objects
However, an incorrect mirror made many of Hubble’s images useless
Image processing techniques were used to fix this
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Examples: Artistic Effects
Artistic effects are used to make images more visually appealing, to add special effects and to make composite images
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Examples: Medicine Take slice from MRI (Magnetic Resounance Imaging) scan of a heart, and find boundaries between types of tissue
Image with gray levels representing tissue density
Use a suitable filter to highlight edges
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Examples: GIS
Geographic Information Systems
Digital image processing techniques are used extensively to manipulate satellite imagery
Terrain classification (التضاريس)
Meteorology (األرصاد الجوية)
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Examples: Law Enforcement
Image processing techniques are used extensively by law enforcers
Number plate recognition for speed cameras
Fingerprint recognition
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Examples: HCI
Try to make human computer interfaces more natural
Face recognition
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Fundamental steps in digital image processing
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1.Image Acquisition:
(capturing an image in digital form)
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Representation &
Description
Image Enhancemen
t
Object Recognition
Problem Domain
Colour Image
Processing
Image Compression Hanan Hardan 24
2.Image Enhancement: making an image look better in a
subjective way.
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Representation &
Description
Image Enhancemen
t
Object Recognition
Problem Domain
Colour Image
Processing
Image Compression Hanan Hardan 25
3.Image Restoration:
improving the appearance of any image objectively.
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Representation &
Description
Image Enhancemen
t
Object Recognition
Problem Domain
Colour Image
Processing
Image Compression Hanan Hardan 26
4.Morphological Processing: extracting image components that are useful in the
representation and description of shape
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Representation &
Description
Image Enhancemen
t
Object Recognition
Problem Domain
Colour Image
Processing
Image Compression Hanan Hardan 27
5.Segmentation:
partitioning an image into its constituent parts or objects.
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Representation &
Description
Image Enhancemen
t
Object Recognition
Problem Domain
Colour Image
Processing
Image Compression Hanan Hardan 28
6.Object Recognition: assigning a label to an object based on
its descriptors
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Representation &
Description
Image Enhancemen
t
Object Recognition
Problem Domain
Colour Image
Processing
Image Compression Hanan Hardan 29
7.Representation & Description:
boundary representation vs. region representation.
Boundary descriptors vs. region descriptors
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Representation &
Description
Image Enhancemen
t
Object Recognition
Problem Domain
Colour Image
Processing
Image Compression Hanan Hardan 30
8.Image Compression:
reducing the stored and transmitted image data.
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Representation &
Description
Image Enhancemen
t
Object Recognition
Problem Domain
Colour Image
Processing
Image Compression Hanan Hardan 31
9.Colour Image Processing: color models and basic color processing
Image Acquisition
Image Restoration
Morphological Processing
Segmentation
Representation &
Description
Image Enhancemen
t
Object Recognition
Problem Domain
Colour Image
Processing
Image Compression Hanan Hardan 32
