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