This document discusses various applications of advanced graphics including animation, digital image processing, morphing, fractals, and ray tracing. It provides details on animation processes like keyframe specifications and generating in-between frames. Digital image processing techniques include image compression, enhancement/restoration through noise removal filters, and image extraction. Fractals are described as objects that are fractional in dimension and can be exactly, nearly, or statistically self-similar across scales. Ray tracing finds pixel color by tracing light rays reflected back to the viewer.

2. Applications of Advanced Graphics
 Animation
 Digital Image processing
 Morphing
 Fractals
 Ray Tracing

3. Animation
 Art of creating moving images
 Widely used in
education, training, entertainment, advertising.
 Formal definition of computer animation is ”
generation of time sequence of visually changing
objects in their
shapes, colour, orientation, translation, rotation etc.”

4.  Computer animation is divided into two broad
processes.
 To design and creation of animation sequence
 To display animation sequence
In general ,an animation sequence is
designed with the following steps:
1.Storyboard Layout
2.Object Definitions
3.Key-frame specifications
4.Generations of in-between frames

5.  The storyboard is an outline of the action.
 An object definition is given for each participant in
the action.
 A key frame is a detailed drawing of the scene at a
certain time in the animation sequence.
 In-betweens are the intermediate frames.
 Approximately 1500 frames are needed for a clip of
one minute of film.

8.  In practice, the animation is created by three
traditional ways.
 Key frame system- key frame is defined
 Parameterized system- parameter may be degree of
freedom, motion path
- motion path can be linear or non-linear or
random
linear- car on a straight road
non-linear- motion of a cricket ball
random- flying butterfly
 Scripting system – user writes some functions to control
animation.

9. Methods to define motion
 Direct motion specification - clock
 Goal specified motion – cricket ball
 Kinematics motion specification- motion can be
specified by position, velocity, acceleration

10. Morphing

12. Digital Image Processing
 It is composed of finite number of elements.
 Each of these elements consists of location
information and pixel details.
 The digital images may be fun images, medical
images, biometric images, satellite images etc.

13.  Sometimes they contain some noise or some clarity is
needed.
 For doing this, some process is performed on the
images, which is known as Digital Image. Processing.
 The main objectives of digital image processing are:
1) To improve pictorial information
2) To analyze pictorial information
3) To optimize image storage for efficient
representation and transmission.

15. Image processing is divided into
three major categories
1) Image compression
2) Image enhancement and restoration
3) Image extraction

16. 1) Image compression
 Size of digital image is very large
 Difficult to transmit due to large size
 For example, animation series or video.
 For this reason, we need to reduce the size of
the image- it is known as image compression

17. 2) Image enhancement and
restoration
 In this method, the images are processed for data error
detection, removal of noise and distortion occurs
while scanning the picture or recording the scene
 It is used to restore the original scene in the form of
image.

18.  There are two types of noises that can be present in
an image.
 1) Random
 2) Non-random
 Some vital information regarding random pixels is
missing as may happen during scanning of a
picture is known as random noise.
 When some strips or lines disturb the image, it is
known as non-random type of noise.

19. In the noise removal, filtering
techniques are used.
 Linear Filter
 Multidimensional filter
 Median filter
 Laplacian filter
 Gaussian filter
 Mean filter
 Kuwahara filter
 Sigma filter

20.  Other image enhancement tasks are colour and
brightness adjustment etc.
 Ex. Black and white image
 Negative image
 Image with glowing edge
 Blurred image
 Image with different background

21. Image Extraction
 Classify the image into various parts.
 Segmentation and clustering are the methods to
analyze a picture by the classification.

22. Applications of digital image
processing
 Medical science
 Entertainment
 Remote sensing
 Robotics
 Biometrics

23. Fractals
 The objects which are neither 2-dimensional or 3-
dimensional.
 They are in some fractional dimensions like 1.5 and so
on.
 Ex. Clouds, curve, trees, mountains etc.

24. Fractals are divided into three
groups
 1) Exact self-similar fractals
 Exactly identical at different scales
 2) Quasi self-similar fractals
 Nearly identical at different scales
 3) Statistical self-similar fractals
 Have numerical or statistical measures across the scale.

25. Ray tracing
 Finds the colour information of each and every
pixel in the scene by tracing a ray of light that is
reflected back to the viewer’s eye from the pixel
position.

26. Ray tracing