3d image visualization

Presented By: Alok SamantarayBranch: Electronics &

telecommunicationRoll no: 042College: BJB College

CONTENTS1. Introduction2. Why Visualize?3. Methods for 3d Output4. Rendering Techniques5. MATLAB Viewing of 3d graphs and scenes6. Volume Rendering7. Isocontouring8. Hole Detection in 3d models9. Visualization of 3d microscopic images10. Whitepaper Stereoscopic visualization11. Applications of Stereoscopic Visualization12. Advantages and Disadvantages of 3d visualization13. Conclusion

IntroductionData visualization is the mapping of data into a Cartesian

space.The greatest challenge for visualizing data is to find a good

spatial representation.

3d projection:It is any method of mapping data 3d points to a 2d plane.

There are 2 types of projections: Parallel Projection Perspective Projection

Why Visualise?More meaningful than lists of numbers.

People have good visual intuition of dynamics.

Visual check that simulation is correct.

Easier to communicate interesting features of the simulation to others.

Methods for 3D OutputProjection of 3D image onto 2D plane.

3D libraries such as OpenGL or DirectX.

OpenGL: OpenGL is a cross-platform 3D graphics and modelling library

with extremely good hardware support.

OpenGL is a procedural graphics API containing over 200 commands and functions.

OpenGL works in conjunction with other libraries, such as GLUT, for easier implementation.

Rendering Techniques There are mainly 3 steps of rendering: Volume Formation Classification Image Formation

There are 2 methods of rendering:Surface Rendering: This is a binary, not a continuous classification technique. Volumes can be visualized by generating an isosurface.

Volume Rendering: This is a percentage classification technique. Maximum Intensity Projection is a volume rendering technique.

MATLAB Viewing of 3d graphs and scenesMATLAB viewing is composed of two basic areas: Positioning the viewpoint Setting the aspect ratio and relative axis scaling

MATLAB automatically selects a viewpoint that is determined by

whether the plot is 2d or 3d: For 2-d Plots, the default is azimuth=0 deg and elevation=90

deg For 3-d Plots, the default is azimuth= -37.5 deg and

elevation=30 deg

Volume RenderingIt involves the following steps: Forming of an RBGA volume from the data Reconstruction of a continuous function Projecting it onto the 2d viewing plane

There are two implementations of volume rendering:

Ray casting Splatting

IsocontouringIt is a technique where one constructs a

boundary between distinct regions in the data.

It is a natural extension from colour mapping.

There are two steps: Explore the data space Connect the points

Hole Detection in 3d ModelsRetrieval speed can be improvedMore meaningful results can be achieved

There are two methods for hole detection: Ray-Scanning X-Ray inspection

There are three primary stages as follows for detecting holes inside 3d models:

Plane Detection Contour Extraction Hole Identification

Visualization of 3d microscopic images Visualizing 3d microscopic images helps better understand the

data.

Selectively discarding the non-important voxel intensity information.

3d image visualization calls for depth blended views from any angle.

2 methods to display 3d data: Maximal(or minimal) intensity projection Alpha-blended views

3 steps to visualize 3d microscopic images: Segmentation Registration Annotation

Whitepaper Stereoscopic visualization of 3d imagesMost challenging advancement of within the area of 3d

visualization.

4 types of whitepaper stereoscopic visualization:

Anaglyphic Stereo-Projection

Passive Stereo-Projection

Active Stereo-Projection

Auto Stereo-Projection

Applications of stereoscopic VisualizationSingle View: This is dedicated for one spectator. Offers higher rendering quality than multiview

applications. Used in medical sector, in research and development

centres.

Multi View: Stereoscopic content presented to several users. Used in promotion and advertisement branch.

Advantages and Disadvantages of 3d visualization

+Easy to implement on any platform with raster graphics.

-Objects drawn as 2D.

-Hard to determine depth from viewer, (front objects do not obscure rear objects).

-Hard to implement perspective.

-Hard to apply textures.

-Slow as pixel driven.

-Hard initial implementation.

+All methods of depth/ perspective/ texturing looked after.

+Hardware support for drawing so fast.

+Libraries exist for many different platforms.

Conclusion The existing techniques are very distinct approaches to the

problems.

Each offers a selection opportunity since different data types need diverse graphical representation.

There is a lot of research still to be done but the requirement has been identified.

Thus we look forward to a large amount of new and innovative techniques for 3d visualization of data and information in the future.

Thank you!!!