METHOD AND APPARATUS FOR DRAWING THICK GRAPHIC PRIMITIVES

Patent №

US 6,930,686

Granted

2005-08-16

Filed 1999

Owner

INTERNATIONAL BUSINESS MACHINES CORPORATION

AI components

1

vision

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

09335289

A graphics system and method with which thick graphic primitives are efficiently drawn by minimizing dependence on drawing algorithms that require appreciable setup time. The method contemplates drawing a thick primitive in which an offset or displacement value is first calculated, based upon the thickness of the graphic primitive. The offset is approximately one half of the thickness of the primitive. Following calculation of the offset value, line drawing parameter values are determined for a line that is parallel to the origin line and displaced from the origin line in a minor axis direction by the displacement or offset value. A loop is then repeated for each grip point in the major axis range of the line. The loop includes an initial step in which a boundary pixel of the thick graphic primitive is drawn using the line drawing algorithm and the line drawing parameter values calculated for the offset line. After the boundary pixel has been drawn, one or more adjacent pixels are drawn using a stepping routine in which the mirior axis coordinate of the selected pixel is either decremented or incremented, depending upon the slope of the line, to write the pixels adjacent the boundary pixel. In this fashion, the present invention draws a thick primitive as a sequence of segments that are parallel to the minor axis of the origin line. In the preferred embodiment, the line drawing routine is preferably comprised of a Bresenham line drawing algorithm or a similar derivative algorithm. In the preferred embodiment, the displacement D is equal to FLOOR((W−1)/2), where W is the thickness of the primitive and FLOOR(X) is the integer portion of X.

VisionG06T 11/203G06T 11/23

AI classification

Vision0.97
Knowledge representation0.00
Speech0.00
AI hardware0.00
Evolutionary computation0.00
Natural language0.00
Machine learning0.00
Planning0.00

Ownership

INTERNATIONAL BUSINESS MACHINES CORPORATION

assignment · 100450071

Assignors

ARANDA, MICHAEL A., BUI, THUY-LINH T., KENNAN, JAMES B., III, PATEL, TUSHAR R.

On an employer assignment, the assignors are typically the inventors.

From the same owner

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