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# visible surface detection methods in computer graphics

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## Visible Surface Detection in Computer Graphics Tutorial 25 November 2022

Visible Surface Detection in Computer Graphics - Visible Surface Detection in Computer Graphics courses with reference manuals and examples pdf.

## VISIBLE SURFACE DETECTION - COMPUTER GRAPHICS

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## What is visible Surface detection?

When a picture that contains the non-transparent objects and surfaces are viewed, the objects that are behind the objects that are closer cannot be viewed. To obtain a realistic screen image, these hidden surfaces need to be removed. This process of identification and removal of these surfaces is known as Hidden-surface problem.

The hidden surface problems can be solved by two methods − Object-Space method and Image-space method. In physical coordinate system, object-space method is implemented and in case of screen coordinate system, image-space method is implemented.

When a 3D object need to be displayed on the 2D screen, the parts of the screen that are visible from the chosen viewing position is identified.

## What is Depth Buffer (Z-Buffer) Method?

It is an image-space approach developed by Cutmull. The Z-depth of each surface is tested for determining the closest surface.

Across the surface, one pixel position is processed at a time. The colour that is to be displayed on the frame buffer is determined by the closest (smallest z) surface, by comparing the depth values for a pixel.

The closer polygons are override by using two buffers namely frame buffer and depth buffer.

Depth buffer is used to store depth values for (x, y) position, as surfaces are processed (0 ≤ depth ≤ 1).

The frame buffer is used to store the intensity value of color value at each position (x, y).

The z-coordinates are usually normalized to the range [0, 1]. The 0 value for z-coordinate indicates back clipping pane and 1 value for z-coordinates indicates front clipping pane.

### Algorithm

Step-1 – Buffer values are set as −

Depthbuffer (x, y) = 0

Framebuffer (x, y) = background color

Step-2 – Each polygon is processed one at a time.

For each projected (x, y) pixel position of a polygon, calculate depth z.

If Z > depthbuffer (x, y)

Compute surface color,

set depthbuffer (x, y) = z,

framebuffer (x, y) = surfacecolor (x, y)

Implementation is easy.

The problems related to speed is reduced once it is implemented in the hardware.

It processes one object at a time.

Large memory is required.

It is a time consuming process.

## What is Scan-Line Method?

The visible surface is identified by the image-space method. All the polygons intersecting need to be grouped and processed for a particular scan-line before processing the next scan-line. This is done by maintaining two tables’ edge table and polygon table.

The Edge Table − It contains coordinate endpoints of each line in the scene, the inverse slope of each line, and pointers into the polygon table to connect edges to surfaces.The Polygon Table − It contains the plane coefficients, surface material properties, other surface data, and may be pointers to the edge table.

The search for the surfaces that cross a given scan line can be facilitated by an active list of edges. Only the edges that cross the scan line is stored by the active list. For indicating whether the position along a scan line is inside or outside the surface, a flag is set.

Each of the scan line is processes from left to right. The surface flag is turned on at left intersection and at right intersection it is turned off.

## What is Area-Subdivision Method?

The view areas are located by representing a part or single surface. The total viewing area is divided into smaller and smaller rectangles until each of the small area is projected as a part of single surface.

This process is continues till all the subdivisions are analyzed to a single surface. This is done by dividing the area into four equal parts. With a specified area boundary there are four relationships:

Surrounding surface − One that completely encloses the area.Overlapping surface − One that is partly inside and partly outside the area.Inside surface − One that is completely inside the area.Outside surface − One that is completely outside the area.

The surface visibility within an area is determined can be tested by stating in terms of the above four classification. If any one of the following conditions is true, the subdivisions of the area are not required.

All surfaces are outside surfaces with respect to the area.

Only one inside, overlapping or surrounding surface is in the area.

A surrounding surface obscures all other surfaces within the area boundaries.

## What is Back-Face Detection?

The back faces of the polyhedron are identified on the basis of “inside-outside” tests. A point (x, y, z) is "inside" a polygon surface with plane parameters A, B, C, and D if When an inside point is along the line of sight to the surface, the polygon must be a back face.

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## Visible Surface Detection

Visible Surface Detection, When we view a picture containing non-transparent objects and surfaces, then we cannot see those objects from view which are behind from objects closer to eye.

## Visible Surface Detection

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When we view a picture containing non-transparent objects and surfaces, then we cannot see those objects from view which are behind from objects closer to eye. We must remove these hidden surfaces to get a realistic screen image. The identification and removal of these surfaces is called Hidden-surface problem.

There are two approaches for removing hidden surface problems − Object-Space method and Image-space method. The Object-space method is implemented in physical coordinate system and image-space method is implemented in screen coordinate system.

When we want to display a 3D object on a 2D screen, we need to identify those parts of a screen that are visible from a chosen viewing position.

Depth Buffer

Z−Buffer Z−Buffer Method

This method is developed by Cutmull. It is an image-space approach. The basic idea is to test the Z-depth of each surface to determine the closest

visible visible surface.

In this method each surface is processed separately one pixel position at a time across the surface. The depth values for a pixel are compared and the closest

smallestz smallestz

surface determines the color to be displayed in the frame buffer.

It is applied very efficiently on surfaces of polygon. Surfaces can be processed in any order. To override the closer polygons from the far ones, two buffers named frame buffer and depth buffer, are used.

Depth buffer is used to store depth values for

x,y x,y

position, as surfaces are processed

0≤depth≤1 0≤depth≤1 .

The frame buffer is used to store the intensity value of color value at each position

x,y x,y .

The z-coordinates are usually normalized to the range [0, 1]. The 0 value for z-coordinate indicates back clipping pane and 1 value for z-coordinates indicates front clipping pane.

### Algorithm

Step-1 − Set the buffer values −

Depthbuffer x,y x,y = 0 Framebuffer x,y x,y = background color

Step-2 − Process each polygon

Oneatatime Oneatatime For each projected x,y x,y

pixel position of a polygon, calculate depth z.

If Z > depthbuffer x,y x,y

Compute surface color,

set depthbuffer x,y x,y = z, framebuffer x,y x,y = surfacecolor x,y x,y

It is easy to implement.

It reduces the speed problem if implemented in hardware.

It processes one object at a time.

It requires large memory.

It is time consuming process.

## Scan-Line Method

It is an image-space method to identify visible surface. This method has a depth information for only single scan-line. In order to require one scan-line of depth values, we must group and process all polygons intersecting a given scan-line at the same time before processing the next scan-line. Two important tables, edge table and polygon table, are maintained for this.

The Edge Table − It contains coordinate endpoints of each line in the scene, the inverse slope of each line, and pointers into the polygon table to connect edges to surfaces.The Polygon Table − It contains the plane coefficients, surface material properties, other surface data, and may be pointers to the edge table.

To facilitate the search for surfaces crossing a given scan-line, an active list of edges is formed. The active list stores only those edges that cross the scan-line in order of increasing x. Also a flag is set for each surface to indicate whether a position along a scan-line is either inside or outside the surface.

Pixel positions across each scan-line are processed from left to right. At the left intersection with a surface, the surface flag is turned on and at the right, the flag is turned off. You only need to perform depth calculations when multiple surfaces have their flags turned on at a certain scan-line position.

## Area-Subdivision Method

The area-subdivision method takes advantage by locating those view areas that represent part of a single surface. Divide the total viewing area into smaller and smaller rectangles until each small area is the projection of part of a single visible surface or no surface at all.

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## Computer Graphics Hidden Surface Removal

Computer Graphics Hidden Surface Removal with Computer Graphics Tutorial, Line Generation Algorithm, 2D Transformation, 3D Computer Graphics, Types of Curves, Surfaces, Computer Animation, Animation Techniques, Keyframing, Fractals etc.

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## Hidden Surface Removal

One of the most challenging problems in computer graphics is the removal of hidden parts from images of solid objects.

In real life, the opaque material of these objects obstructs the light rays from hidden parts and prevents us from seeing them.

In the computer generation, no such automatic elimination takes place when objects are projected onto the screen coordinate system.

Instead, all parts of every object, including many parts that should be invisible are displayed.

To remove these parts to create a more realistic image, we must apply a hidden line or hidden surface algorithm to set of objects.

The algorithm operates on different kinds of scene models, generate various forms of output or cater to images of different complexities.

All use some form of geometric sorting to distinguish visible parts of objects from those that are hidden.

Just as alphabetical sorting is used to differentiate words near the beginning of the alphabet from those near the ends.

Geometric sorting locates objects that lie near the observer and are therefore visible.

Hidden line and Hidden surface algorithms capitalize on various forms of coherence to reduce the computing required to generate an image.

Different types of coherence are related to different forms of order or regularity in the image.

Scan line coherence arises because the display of a scan line in a raster image is usually very similar to the display of the preceding scan line.

Frame coherence in a sequence of images designed to show motion recognizes that successive frames are very similar.Object coherence results from relationships between different objects or between separate parts of the same objects.

A hidden surface algorithm is generally designed to exploit one or more of these coherence properties to increase efficiency.

Hidden surface algorithm bears a strong resemblance to two-dimensional scan conversions.

## Types of hidden surface detection algorithms

Object space methods

Image space methods

Object space methods: In this method, various parts of objects are compared. After comparison visible, invisible or hardly visible surface is determined. These methods generally decide visible surface. In the wireframe model, these are used to determine a visible line. So these algorithms are line based instead of surface based. Method proceeds by determination of parts of an object whose view is obstructed by other object and draws these parts in the same color.Image space methods: Here positions of various pixels are determined. It is used to locate the visible surface instead of a visible line. Each point is detected for its visibility. If a point is visible, then the pixel is on, otherwise off. So the object close to the viewer that is pierced by a projector through a pixel is determined. That pixel is drawn is appropriate color.

These methods are also called a Visible Surface Determination. The implementation of these methods on a computer requires a lot of processing time and processing power of the computer.

The image space method requires more computations. Each object is defined clearly. Visibility of each object surface is also determined.

## Differentiate between Object space and Image space method

Object Space Image Space

1. Image space is object based. It concentrates on geometrical relation among objects in the scene. 1. It is a pixel-based method. It is concerned with the final image, what is visible within each raster pixel.

2. Here surface visibility is determined. 2. Here line visibility or point visibility is determined.

3. It is performed at the precision with which each object is defined, No resolution is considered. 3. It is performed using the resolution of the display device.

4. Calculations are not based on the resolution of the display so change of object can be easily adjusted. 4. Calculations are resolution base, so the change is difficult to adjust.

5. These were developed for vector graphics system. 5. These are developed for raster devices.

6. Object-based algorithms operate on continuous object data. 6. These operate on object data.

7. Vector display used for object method has large address space. 7. Raster systems used for image space methods have limited address space.

8. Object precision is used for application where speed is required. 8. There are suitable for application where accuracy is required.

9. It requires a lot of calculations if the image is to enlarge. 9. Image can be enlarged without losing accuracy.

10. If the number of objects in the scene increases, computation time also increases. 10. In this method complexity increase with the complexity of visible parts.

## Similarity of object and Image space method

In both method sorting is used a depth comparison of individual lines, surfaces are objected to their distances from the view plane.

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