This document discusses key concepts in applied computer vision and digital image processing. It defines common terms like digital image, image processing, and computer vision. It also describes how digital images are represented, including binary images with 1 bit per pixel, 8-bit gray-level images, and 24-bit color images with separate red, green, and blue channels. Additionally, it lists common image parameter values and types of image neighborhoods and operations involved in digital image representation.

1. Applied Computer Vision

2. Content of this PPT is based on the following resources,
1. Practical Image and Video Processing using MATLAB, Oge
Marques, Florida Atlantic University, Wiley-IEEE Press, 2011,
ISBN: 978-0-470-04815-3
2. http://ultra.sdk.free.fr/docs/Image-
Processing/Image%20processing%20theory/Fundamentals%2
0Of%20Image%20Processing.pdf

3. Basic Terminologies
 Image - Digital Image
 Digital Image Processing
 Computer Vision

4. Digital Image Definitions
• Image Processing -> image in - image out
• Image Analysis -> image in - measurements out
• Image Understanding -> image in - high-level description out

5. Positions,
depth, color,
and time

6. Common values of digital image parameters
(values depend on video standards)

7. Image operations

8. Graphical representation of image
operations

9. Types of neighborhoods
 Rectangular sampling
 Hexagonal sampling

10. Rectangular
sampling
4-connected
Hexagonal
sampling
connected
6-connected
Rectangular
sampling
8-connected

12. Digital Image Representation

14. Image types
• Binary (1-Bit) Images
• Gray-Level (8-Bit) Images
• Color Images

15. Binary images are encoded as a 2D array, typically using 1 bit per
pixel, where a 0 usually means “black” and a 1 means “white”
Binary image

16. Gray level (8-bit) image
• Gray-level (monochrome) images are also encoded as a 2D array of pixels, usually with 8 bits per
pixel,
• 0 corresponds to “black,” a pixel value of 255 means “white,” and intermediate values indicate
varying shades of gray.
• The total number of gray levels is larger than the human visual system
requirements (which, in most cases, cannot appreciate any improvements beyond 64
gray levels)

17. Color image
• 24-Bit (RGB) Color Images Color images represented using three 2D arrays of same size, one for
each color channel: red (R), green (G), and blue (B).
• Each array element contains an 8-bit value, indicating the amount of red, green, or blue at that point
in a [0, 255] scale.
• The combination of the three 8-bit values into a 24-bit number allows 224 (16,777,216, usually
referred to as 16 million or 16 M) color combinations.