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CS 602 Computer Graphics Assignment No 3 Solution & Discussion Due Date:12-06-2012

Q No. 1

             Discuss the advantages and disadvantages of Gouraud shading.    10


Q  No. 2  

             Discuss the “the H test” (highlight detection) in reference of Gouraud          and  Phong shading?                                                                              10


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Replies to This Discussion

Please Discuss here about this assignment.Thanks

Advantages of Gouraud shading:

Gouraud shading gives a much better image than faceted shading (the facets no longer visible). It is not too computationally expensive: one floating point addition (for each color) for each pixel. (the mapping to actual display registers requires a floating point multiplication)

Disadvantages to Gouraud shading:

It eliminates creases that you may want to preserve, e.g. in a cube. We can modify data structure to prevent this by storing each physical vertex 3 times, i.e. a different logical vertex for each polygon

 by asma

heeeeee see this

solution for second question

Generally, an object will have relatively few highlighted polygons, so it would be computationally more efficient to Phong shade the highlighted polygons, and to Gouraud shade the remainder. In practice, however, the diffuse components produced for a particular pixel by the two interpolation methods differ slightly, and it is necessary to Gouraud shade the entire object. The Phong specular term is then evaluated on the highlighted polygons, and combined with the Gouraud diffuse value.


To enable the implementation of the combined shading algorithm, a test has to be determined to ascertain which of the polygons are partially or fully within an area of specular light. This test is known as the highlight test or H test.


The highlight detection is based on a hierarchy of simple tests that predict the value of the highlight function on the line between two vertices. For there to be a contribution from the specular term N.H (vector H is the halfway vector) we can say:


N.H ≥ T


where T is a threshold term. The value of this term is examined at pair of vertices to predict the variation in its magnitude along the edge. A hierarchy of five simple tests performs this prediction:



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