it is a Visible surface detection method is also known as depth buffer method. In this method detect the visible surface by using the distance of the object from the projections plane.
The depth buffer method is used to determine visibility in 3D graphics by testing the depth (z-coordinate) of each surface to determine the closest visible surface. It involves using two buffers - a depth buffer to store the depth values and a frame buffer to store color values. For each pixel, the depth value is calculated and compared to the existing value in the depth buffer, and if closer the color and depth values are updated in the respective buffers. This method is implemented efficiently in hardware and processes surfaces one at a time in any order.
Visible surface detection in computer graphicanku2266
Visible surface detection aims to determine which parts of 3D objects are visible and which are obscured. There are two main approaches: object space methods compare objects' positions to determine visibility, while image space methods process surfaces one pixel at a time to determine visibility based on depth. Depth-buffer and A-buffer methods are common image space techniques that use depth testing to handle occlusion.
The Cohen-Sutherland algorithm divides the plane into 9 regions and uses 4-bit codes to encode whether each endpoint of a line segment is left, right, above, or below the clipping window. It then uses the endpoint codes to either trivially accept or reject the line segment, or perform clipping by calculating the intersection point of the line with the window boundary and replacing the outside endpoint. The main steps are to assign codes to endpoints, AND the codes to check for trivial acceptance or rejection, clip by replacing outside endpoints if needed, and repeating for other line segments.
Identify those parts of a scene that are visible from a chosen viewing position.
Visible-surface detection algorithms are broadly classified according to whether
they deal with object definitions directly or with their projected images.
These two approaches are called object-space methods and image-space methods, respectively
An object-space method compares
objects and parts of objects to each other within the scene definition to determine which surfaces, as a whole, we should label as visible.
In an image-space algorithm, visibility is decided point by point at each pixel position on the projection plane.
The document discusses different techniques for filling polygons, including boundary fill, flood fill, and scan-line fill methods. It provides details on how each technique works, such as using a seed point and filling neighboring pixels for boundary fill, replacing all pixels of a selected color for flood fill, and drawing pixels between edge intersections for each scan line for scan-line fill. Examples are given to illustrate the filling process for each method.
The depth buffer method is used to determine visibility in 3D graphics by testing the depth (z-coordinate) of each surface to determine the closest visible surface. It involves using two buffers - a depth buffer to store the depth values and a frame buffer to store color values. For each pixel, the depth value is calculated and compared to the existing value in the depth buffer, and if closer the color and depth values are updated in the respective buffers. This method is implemented efficiently in hardware and processes surfaces one at a time in any order.
Visible surface detection in computer graphicanku2266
Visible surface detection aims to determine which parts of 3D objects are visible and which are obscured. There are two main approaches: object space methods compare objects' positions to determine visibility, while image space methods process surfaces one pixel at a time to determine visibility based on depth. Depth-buffer and A-buffer methods are common image space techniques that use depth testing to handle occlusion.
The Cohen-Sutherland algorithm divides the plane into 9 regions and uses 4-bit codes to encode whether each endpoint of a line segment is left, right, above, or below the clipping window. It then uses the endpoint codes to either trivially accept or reject the line segment, or perform clipping by calculating the intersection point of the line with the window boundary and replacing the outside endpoint. The main steps are to assign codes to endpoints, AND the codes to check for trivial acceptance or rejection, clip by replacing outside endpoints if needed, and repeating for other line segments.
Identify those parts of a scene that are visible from a chosen viewing position.
Visible-surface detection algorithms are broadly classified according to whether
they deal with object definitions directly or with their projected images.
These two approaches are called object-space methods and image-space methods, respectively
An object-space method compares
objects and parts of objects to each other within the scene definition to determine which surfaces, as a whole, we should label as visible.
In an image-space algorithm, visibility is decided point by point at each pixel position on the projection plane.
The document discusses different techniques for filling polygons, including boundary fill, flood fill, and scan-line fill methods. It provides details on how each technique works, such as using a seed point and filling neighboring pixels for boundary fill, replacing all pixels of a selected color for flood fill, and drawing pixels between edge intersections for each scan line for scan-line fill. Examples are given to illustrate the filling process for each method.
This document discusses 2D geometric transformations including translation, rotation, and scaling. It provides the mathematical definitions and matrix representations for each transformation. Translation moves an object along a straight path, rotation moves it along a circular path, and scaling changes its size. All transformations can be represented by 3x3 matrices using homogeneous coordinates to allow combinations of multiple transformations. The inverse of each transformation matrix is also defined.
This document summarizes the scan-line rendering algorithm. It maintains two tables - an edge table containing line coordinates and surface pointers, and a polygon table containing surface properties. For each scan line, all intersecting surfaces are examined to determine the visible surface. Depths are calculated to set surface flags and populate the image buffer with intensity values from the visible surface. Coherence between scan lines is exploited to reuse prior visibility calculations where edge intersections remain the same.
Cohen-Sutherland Line Clipping Algorithm:
When drawing a 2D line on screen, it might happen that one or both of the endpoints are outside the screen while a part of the line should still be visible. In that case, an efficient algorithm is needed to find two new endpoints that are on the edges on the screen, so that the part of the line that's visible can now be drawn. This way, all those points of the line outside the screen are clipped away and you don't need to waste any execution time on them.
A good clipping algorithm is the Cohen-Sutherland algorithm for this solution.
By,
Maruf Abdullah Rion
The document discusses 2D viewing and clipping techniques in computer graphics. It describes how clipping is used to select only a portion of an image to display by defining a clipping region. It also discusses 2D viewing transformations which involve operations like translation, rotation and scaling to map coordinates from a world coordinate system to a device coordinate system. It specifically describes the Cohen-Sutherland line clipping algorithm which uses region codes to quickly determine if lines are completely inside, outside or intersect the clipping region to optimize the clipping calculation.
In a raster scan system, the electron beam scans across rows of the screen from top to bottom, turning intensity on and off to illuminate spots and form an image. The image definition is stored in a refresh buffer memory that holds intensity values for screen points. In a random scan system, an application and graphics package are stored in memory, and graphics commands are translated into a display file that a display processor accesses to refresh the screen. Graphics patterns are drawn by directing the electron beam along picture lines one at a time, positioning it between coordinate-defined endpoints to fill each line.
Projection is the transformation of a 3D object into a 2D plane by mapping points from the 3D object to the projection plane. There are two main types of projection: perspective projection and parallel projection. Perspective projection uses lines that converge to a single point, while parallel projection uses parallel lines. Perspective projection includes one-point, two-point, and three-point perspectives. Parallel projection includes orthographic projection, which projects lines perpendicular to the plane, and oblique projection, where lines are parallel but not perpendicular to the plane.
The document describes different algorithms for filling polygon and area shapes, including scanline fill, boundary fill, and flood fill algorithms. The scanline fill algorithm works by determining intersections of boundaries with scanlines and filling color between intersections. Boundary fill works by starting from an interior point and recursively "painting" neighboring points until the boundary is reached. Flood fill replaces a specified interior color. Both can be 4-connected or 8-connected. The document also discusses problems that can occur and more efficient span-based approaches.
Polygon clipping involves taking a polygon and clipping it against another shape to produce one or more smaller polygons. The Sutherland-Hodgman algorithm handles polygon clipping by testing each edge of the clipping polygon against each edge of the clip shape. There are four cases for how an edge can be clipped - wholly inside, exit, wholly outside, enter - and the algorithm saves or discards vertices based on these cases. Repeatedly clipping against each edge of the clip shape handles all cases and produces the final clipped polygon(s).
The document discusses various algorithms for visible surface detection, which is the identification and removal of surfaces that are not visible to the user based on their perspective. It describes the Z-buffer algorithm, BSP algorithm, A-buffer algorithm, scan-line algorithm, and painter's/depth sorting algorithm. For the Z-buffer algorithm, it explains how it uses two buffers (Z-buffer and refresh buffer) to compare depth values of overlapping pixels and determine which surfaces are visible. It also discusses considerations for different viewing directions. The BSP algorithm sorts polygons from back to front using a binary space partitioning tree. The A-buffer improves on Z-buffer for transparent surfaces by using linked lists at each pixel. The scan-line
hidden surface elimination using z buffer algorithmrajivagarwal23dei
The document discusses hidden surface removal techniques used in 3D computer graphics. It introduces the hidden surface problem that arises when non-transparent objects obscure other objects from view. It describes object space and image space methods for identifying and removing hidden surfaces. The z-buffer algorithm is discussed as a commonly used image space method that works by comparing depth values in a z-buffer to determine which surfaces are visible at each pixel location.
The Cyrus-Beck algorithm is used for line clipping against non-rectangular convex polygons. It uses a parametric equation to find the intersection point of the line with the polygon boundary. The algorithm calculates the time values for the line endpoints at each polygon edge, then uses those times in the parametric equation to find the clipped line segment P'0 and P'1 that is visible within the polygon clipping window.
Bresenham's line algorithm is an efficient method for drawing lines on a digital display. It works by calculating the next pixel coordinate along the line using integer math only. This avoids complex floating point calculations. It starts at the initial coordinate and iteratively calculates the next x,y coordinate using integer addition and comparisons until it reaches the final endpoint.
An illumination model, also called a lighting model and sometimes referred to as a shading model, is used to calculate the intensity of light that we should see at a given point on the surface of an object.
The document discusses the 2D viewing pipeline. It describes how a 3D world coordinate scene is constructed and then transformed through a series of steps to 2D device coordinates that can be displayed. These steps include converting to viewing coordinates using a window-to-viewport transformation, then mapping to normalized and finally device coordinates. It also covers techniques for clipping objects and lines that fall outside the viewing window including Cohen-Sutherland line clipping and Sutherland-Hodgeman polygon clipping.
The document discusses different methods for 3D display and projection. It describes parallel projection, where lines of sight are parallel, and perspective projection, where lines converge at vanishing points. The key types of projection are outlined as parallel (orthographic and oblique) and perspective. Orthographic projection uses perpendicular lines, while oblique projection uses arbitrary angles. Perspective projection creates realistic size variation with distance and can have one, two, or three vanishing points.
Clipping identifies portions of a scene outside a specified clip window region. There are different types of clipping for different graphics elements. The Cohen-Sutherland algorithm assigns a binary code to line endpoints based on their position relative to the clip window boundaries, and uses logical AND operations on the codes to determine if a line needs clipping or can be fully accepted or rejected. It iteratively clips portions of a line outside the window until the line is fully processed.
This document discusses various visible surface detection methods in computer graphics. It describes object-space methods like back-face detection that compare object surfaces, and image-space methods like depth buffering that determine visibility point-by-point. Specific algorithms covered include depth buffering, scan-line, depth sorting, BSP trees, ray casting, and methods for curved and wireframe surfaces. It also provides examples and discusses functions for implementing visibility detection in OpenGL.
This document provides an overview of 3D transformations, including translation, rotation, scaling, reflection, and shearing. It explains that 3D transformations generalize 2D transformations by including a z-coordinate and using homogeneous coordinates and 4x4 transformation matrices. Each type of 3D transformation is defined using matrix representations and equations. Rotation is described for each coordinate axis, and reflection is explained for each axis plane. Shearing is introduced as a way to modify object shapes, especially for perspective projections.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
This document discusses 2D geometric transformations including translation, rotation, and scaling. It provides the mathematical definitions and matrix representations for each transformation. Translation moves an object along a straight path, rotation moves it along a circular path, and scaling changes its size. All transformations can be represented by 3x3 matrices using homogeneous coordinates to allow combinations of multiple transformations. The inverse of each transformation matrix is also defined.
This document summarizes the scan-line rendering algorithm. It maintains two tables - an edge table containing line coordinates and surface pointers, and a polygon table containing surface properties. For each scan line, all intersecting surfaces are examined to determine the visible surface. Depths are calculated to set surface flags and populate the image buffer with intensity values from the visible surface. Coherence between scan lines is exploited to reuse prior visibility calculations where edge intersections remain the same.
Cohen-Sutherland Line Clipping Algorithm:
When drawing a 2D line on screen, it might happen that one or both of the endpoints are outside the screen while a part of the line should still be visible. In that case, an efficient algorithm is needed to find two new endpoints that are on the edges on the screen, so that the part of the line that's visible can now be drawn. This way, all those points of the line outside the screen are clipped away and you don't need to waste any execution time on them.
A good clipping algorithm is the Cohen-Sutherland algorithm for this solution.
By,
Maruf Abdullah Rion
The document discusses 2D viewing and clipping techniques in computer graphics. It describes how clipping is used to select only a portion of an image to display by defining a clipping region. It also discusses 2D viewing transformations which involve operations like translation, rotation and scaling to map coordinates from a world coordinate system to a device coordinate system. It specifically describes the Cohen-Sutherland line clipping algorithm which uses region codes to quickly determine if lines are completely inside, outside or intersect the clipping region to optimize the clipping calculation.
In a raster scan system, the electron beam scans across rows of the screen from top to bottom, turning intensity on and off to illuminate spots and form an image. The image definition is stored in a refresh buffer memory that holds intensity values for screen points. In a random scan system, an application and graphics package are stored in memory, and graphics commands are translated into a display file that a display processor accesses to refresh the screen. Graphics patterns are drawn by directing the electron beam along picture lines one at a time, positioning it between coordinate-defined endpoints to fill each line.
Projection is the transformation of a 3D object into a 2D plane by mapping points from the 3D object to the projection plane. There are two main types of projection: perspective projection and parallel projection. Perspective projection uses lines that converge to a single point, while parallel projection uses parallel lines. Perspective projection includes one-point, two-point, and three-point perspectives. Parallel projection includes orthographic projection, which projects lines perpendicular to the plane, and oblique projection, where lines are parallel but not perpendicular to the plane.
The document describes different algorithms for filling polygon and area shapes, including scanline fill, boundary fill, and flood fill algorithms. The scanline fill algorithm works by determining intersections of boundaries with scanlines and filling color between intersections. Boundary fill works by starting from an interior point and recursively "painting" neighboring points until the boundary is reached. Flood fill replaces a specified interior color. Both can be 4-connected or 8-connected. The document also discusses problems that can occur and more efficient span-based approaches.
Polygon clipping involves taking a polygon and clipping it against another shape to produce one or more smaller polygons. The Sutherland-Hodgman algorithm handles polygon clipping by testing each edge of the clipping polygon against each edge of the clip shape. There are four cases for how an edge can be clipped - wholly inside, exit, wholly outside, enter - and the algorithm saves or discards vertices based on these cases. Repeatedly clipping against each edge of the clip shape handles all cases and produces the final clipped polygon(s).
The document discusses various algorithms for visible surface detection, which is the identification and removal of surfaces that are not visible to the user based on their perspective. It describes the Z-buffer algorithm, BSP algorithm, A-buffer algorithm, scan-line algorithm, and painter's/depth sorting algorithm. For the Z-buffer algorithm, it explains how it uses two buffers (Z-buffer and refresh buffer) to compare depth values of overlapping pixels and determine which surfaces are visible. It also discusses considerations for different viewing directions. The BSP algorithm sorts polygons from back to front using a binary space partitioning tree. The A-buffer improves on Z-buffer for transparent surfaces by using linked lists at each pixel. The scan-line
hidden surface elimination using z buffer algorithmrajivagarwal23dei
The document discusses hidden surface removal techniques used in 3D computer graphics. It introduces the hidden surface problem that arises when non-transparent objects obscure other objects from view. It describes object space and image space methods for identifying and removing hidden surfaces. The z-buffer algorithm is discussed as a commonly used image space method that works by comparing depth values in a z-buffer to determine which surfaces are visible at each pixel location.
The Cyrus-Beck algorithm is used for line clipping against non-rectangular convex polygons. It uses a parametric equation to find the intersection point of the line with the polygon boundary. The algorithm calculates the time values for the line endpoints at each polygon edge, then uses those times in the parametric equation to find the clipped line segment P'0 and P'1 that is visible within the polygon clipping window.
Bresenham's line algorithm is an efficient method for drawing lines on a digital display. It works by calculating the next pixel coordinate along the line using integer math only. This avoids complex floating point calculations. It starts at the initial coordinate and iteratively calculates the next x,y coordinate using integer addition and comparisons until it reaches the final endpoint.
An illumination model, also called a lighting model and sometimes referred to as a shading model, is used to calculate the intensity of light that we should see at a given point on the surface of an object.
The document discusses the 2D viewing pipeline. It describes how a 3D world coordinate scene is constructed and then transformed through a series of steps to 2D device coordinates that can be displayed. These steps include converting to viewing coordinates using a window-to-viewport transformation, then mapping to normalized and finally device coordinates. It also covers techniques for clipping objects and lines that fall outside the viewing window including Cohen-Sutherland line clipping and Sutherland-Hodgeman polygon clipping.
The document discusses different methods for 3D display and projection. It describes parallel projection, where lines of sight are parallel, and perspective projection, where lines converge at vanishing points. The key types of projection are outlined as parallel (orthographic and oblique) and perspective. Orthographic projection uses perpendicular lines, while oblique projection uses arbitrary angles. Perspective projection creates realistic size variation with distance and can have one, two, or three vanishing points.
Clipping identifies portions of a scene outside a specified clip window region. There are different types of clipping for different graphics elements. The Cohen-Sutherland algorithm assigns a binary code to line endpoints based on their position relative to the clip window boundaries, and uses logical AND operations on the codes to determine if a line needs clipping or can be fully accepted or rejected. It iteratively clips portions of a line outside the window until the line is fully processed.
This document discusses various visible surface detection methods in computer graphics. It describes object-space methods like back-face detection that compare object surfaces, and image-space methods like depth buffering that determine visibility point-by-point. Specific algorithms covered include depth buffering, scan-line, depth sorting, BSP trees, ray casting, and methods for curved and wireframe surfaces. It also provides examples and discusses functions for implementing visibility detection in OpenGL.
This document provides an overview of 3D transformations, including translation, rotation, scaling, reflection, and shearing. It explains that 3D transformations generalize 2D transformations by including a z-coordinate and using homogeneous coordinates and 4x4 transformation matrices. Each type of 3D transformation is defined using matrix representations and equations. Rotation is described for each coordinate axis, and reflection is explained for each axis plane. Shearing is introduced as a way to modify object shapes, especially for perspective projections.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
Your Skill Boost Masterclass: Strategies for Effective Upskilling
Z buffer
1. A. K. Biswas, Dept. Of Computer Apllication, B.I.T., Durg 1
COMPUTER GRAPHICSCOMPUTER GRAPHICS
Visible Surface DetectionVisible Surface Detection
(Z-Buffer/Depth Buffer)(Z-Buffer/Depth Buffer)
2. A. K. Biswas, Dept. Of Computer Apllication, B.I.T., Durg 2
DEPTH-BUFFER METHODDEPTH-BUFFER METHOD
Compares surface depth values throughout a scene
for each pixel position on the projection plane
Usually applied to scenes only containing polygons
Fast approach due to easy depth values computation
Also often called the z-buffer method
(x2, y2) & z2
(x3, y3) & z3
(x1, y1) & z1
(x1, y1), (x2, y2) &
(x3, y3) are the pixel
positions of surfaces
S1, S2, and S3
respectively.
z1, z2 and z3 defines
the depth values
(distance) of surfaces
S1, S2, and S3
respectively from the
View Plane
3. A. K. Biswas, Dept. Of Computer Apllication, B.I.T., Durg 3
DEPTH-BUFFER METHOD (Cont…)DEPTH-BUFFER METHOD (Cont…)
1. Initialise the depth buffer and frame buffer so that for
all buffer positions (x, y)
depthBuff(x, y) = 1.0
frameBuff(x, y) = bgColour
2. Process each polygon in a scene, one at a time
– For each projected (x, y) pixel position of a
polygon, calculate the depth z (if not already
known)
– If z < depthBuff(x, y), compute the surface colour
at that position and set
depthBuff(x, y) = z
frameBuff(x, y) = surfColour(x, y)
After all surfaces are processed depthBuff and frameBuff
will store correct values
4. A. K. Biswas, Dept. Of Computer Apllication, B.I.T., Durg 4
DEPTH CALCULATIONDEPTH CALCULATION
7. A. K. Biswas, Dept. Of Computer Apllication, B.I.T., Durg 7
Iterative Calculations (cont…)Iterative Calculations (cont…)
top scan line
bottom scan line
y scan line
y - 1 scan line
x x’
8. A. K. Biswas, Dept. Of Computer Apllication, B.I.T., Durg 8
DISADVANTAGES OF DEPTH BUFFERDISADVANTAGES OF DEPTH BUFFER
This method only find out one visible surface
at each pixel position that means it deals
with only Opaque surface.
1
2
3
4
5
6
1 Red
2 Red
3 Green
4 Blue
5 Green
6 Red