Date post: | 19-Jan-2016 |
Category: |
Documents |
Upload: | marjory-berry |
View: | 346 times |
Download: | 30 times |
Image Processing
Ch1: Introduction
Prepared by: Hanan Hardan
Introduction
“One picture is worth more than ten thousand words”
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
Available online at:homepages.inf.ed.ac.uk/rbf/BOOKS/VERNON/
ContentsThis lecture will cover:
What is a digital image? What is digital image processing? History of digital image processing State of the art examples of digital image
processing Key stages in digital image processing
What is a Digital Image?A digital image: is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels
What is a Digital Image? (cont…)
Pixels: Elements of the digital image , each has intensity.
Intensity of pixel: the amplitudeغزارة of gray level (in gray scale images)
1 pixel
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
Digital image is composed of a finite number of elements, each one has a particular location and value.. These element are called picture elements, image elements or pixels.
Note: images can be: binary, grayscale, color.
digital image processing
What is digital Image?
What is digital image?The image consists of finite number of pixels ( f(x,y) )
pixel
Every pixel Is an intersection تقاطع between a row and a column.
every pixel has intensity كثافة
Ex:
f(4,3)= 123
Refers to a pixel existing on the intersection between row 4 with column 3, and its intensity is 123.
Remember digitization implies that a digital image is an approximation of a real scene
digital image processing
Binary ImagesBinary images are images that have been quantized to two values, usually denoted 0 and 1, but often with pixel values 0 and 255, representing black and white .
Remember: images can be: binary, grayscale, color.
digital image processing
Binary Images
Grayscale Images A grayscale (or graylevel) image is simply
one in which the only colors are shades of gray (0 – 255)
Grayscale Images
Color Images Color image: A color image contains pixels
each of which holds three intensity values corresponding to the red, green, and blue or( RGB)
Color Images
What is digital image processing?
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
digital image processing
1. Computer Graphics: the creation of image2. Image processing: enhancement or other
manipulation of the image3. Computer vision: analysis of the content
Image processing fields:
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
تحسينها نريد قديمة صورة مثال
digital image processing
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
حوافه: لنبرز حاسوبيا تعديلها نريد لكرسي صورة مثال
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
عليه: يتعرف ان الحاسوب نريد فيه لمشتبه صورة مثال
Uses of DIP Image enhancement/restoration Artistic effects Medical visualisation Law enforcement Human computer interfaces
Examples: Image Enhancement One of the most common uses of DIP
techniques: improve quality, remove noise etc
Examples: The Hubble TelescopeLaunched in 1990 the Hubble telescope can take images of very distant objectsHowever, an incorrect mirror made many of Hubble’s images uselessImage processing techniques were used to fix this
Examples: Artistic Effects Artistic effects are used to make images
more visually appealing, to add special effects and to make composite images
Examples: MedicineTake 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
Examples: GISGeographic Information Systems
Digital image processing techniques are used extensively to manipulate satellite imagery
Terrain classification (التضاريس) Meteorology (األرصاد الجوية)
Examples: Law EnforcementImage processing techniques are used extensively by law enforcers
Number plate recognition for speed cameras Fingerprint recognition
Examples: HCITry to make human computer interfaces more natural
Face recognition
Fundamental steps in digital image processing
Fundamental steps in digital image processing
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
Fundamental Steps in DIPStep 1: Image Acquisition
The image is captured by a sensor (eg. Camera), and digitized if the output of the camera or sensor is not already in digital form, using analogue-to-digital convertor
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
Fundamental Steps in DIPStep 2: Image Enhancement The process of manipulating an image so
that the result is more suitable than the original for specific applications.
Enhancement techniques are so varied, and use so many different image processing approaches
The idea behind enhancement techniques is to bring out details that are hidden, or simple to highlight certain features of interest in an image.
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
Fundamental Steps in DIP
Step 3: Image Restoration- Improving the appearance of an image
( طبيعتها الى الصوره اعادة (محاولة- Tend to be based on mathematical or probabilistic models of image degradation.
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
Fundamental Steps in DIPStep4 : Morphological Processing
Tools for extracting image components that are useful in the representation and description of shape.
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
Fundamental Steps in DIPStep 5: Image Segmentation
Segmentation procedures partition an image into its parts or objects.
Computer tries to separate objects from the image background.الصورة: تشكيل العادة او المهمه االجزاء على الحصول الهدف
معنى لتعطيمختلف
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
Fundamental Steps in DIPStep6 : Recognition and Interpretation
Recognition: the process that assigns label to an object based on the information provided by its description.
الصوره محتوى تميز
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
Fundamental Steps in DIPStep 7: Representation and DescriptionMake a decision whether the data should be
represented as a boundary or as a complete region:
Boundary representation: focus on external shape characteristics, such as corners and inflections.
Region representation: focus on internal properties, such as texture or skeleton shape
ووصفها الصوره تمثيل
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
Fundamental Steps in DIPStep 8: Compression
Techniques for reducing the storage required to save an image or the bandwidth required to transmit it.
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
Fundamental Steps in DIPStep 9: Colour Image Processing
Use the colour of the image to extract features of interest in an image