Image Processing Reference
Some of the first applications of digital video and image processing were to im-
prove the quality of the captured images, but as the power of computers grew, so did
the number of applications where video and image processing could make a differ-
ence. Today, video and image processing are used in many diverse applications, such
as astronomy (to enhance the quality), medicine (to measure and understand some
parameters of the human body, e.g., blood flow in fractured veins), image compres-
sion (to reduce the memory requirement when storing an image), sports (to capture
the motion of an athlete in order to understand and improve the performance), re-
habilitation (to assess the locomotion abilities), motion pictures (to capture actors'
motion in order to produce special effects based on graphics), surveillance (detect
and track individuals and vehicles), production industries (to assess the quality of
products), robot control (to detect objects and their pose so a robot can pick them
up), TV productions (mixing graphics and live video, e.g., weather forecast), bio-
metrics (to measure some unique parameters of a person), photo editing (improving
the quality or adding effects to photographs), etc.
Many of these applications rely on the same video and image processing meth-
ods, and it is these basic methods which are the focus of this topic.
The Different Flavors of Video and Image Processing
The different video and image processing methods are often grouped into the cate-
gories listed below. There is no unique definition of the different categories and to
make matters worse they also overlap significantly. Here is one set of definitions:
Video and Image Compression This is probably the most well defined category
and contains the group of methods used for compressing video and image data.
Image Manipulation This category covers methods used to edit an image. For ex-
ample, when rotating or scaling an image, but also when improving the quality by
for example changing the contrast.
Image Processing Image processing originates from the more general field of sig-
nal processing and covers methods used to segment the object of interest. Seg-
mentation here refers to methods which in some way enhance the object while
suppressing the rest of the image (for example the edges in an image).
Video Processing Video processing covers most of the image processing methods,
but also includes methods where the temporal nature of video data is exploited.
Image Analysis Here the goal is to analyze the image with the purpose of first
finding objects of interest and then extracting some parameters of these objects.
For example, finding an object's position and size.
Machine Vision When applying video processing, image processing or image
analysis in production industries it is normally referred to as machine vision or
simply vision .
Computer Vision Humans have human vision and similarly a computer has com-
puter vision . When talking about computer vision we normally mean advanced
algorithms similar to those a human can perform, e.g., face recognition. Normally
computer vision also covers all methods where more than one camera is applied.