Title :
Least-squares font metric estimation from images
Author_Institution :
Xerox Palo Alto Res. Center, CA, USA
fDate :
10/1/1993 12:00:00 AM
Abstract :
The problem of determining font metrics from measurements on images of typeset text is discussed, and least-squares procedures for font metric estimation are developed. When it is shown that kerning is not present, sidebearing estimation involves solving a set of linear equations, called the sidebearing normal equations. More generally, simultaneous sidebearing and kerning term estimation involves an iterative procedure in which a modified set of sidebearing normal equations is solved during each iteration. Character depth estimates are obtained by solving a set of baseline normal equations. In a preliminary evaluation of the proposed procedures on scanned text images in three fonts, the root-mean-square set width estimation error was about 0.2 pixel. An application of font metric estimation to text image editing is discussed
Keywords :
image processing; iterative methods; least squares approximations; text editing; baseline normal equations; character depth estimation; character positioning; font metric estimation; iterative procedure; kerning term estimation; least-squares procedures; root-mean-square set width estimation error; scanned text images; sidebearing estimation; sidebearing normal equations; text image editing; typeset text; Decoding; Equations; Estimation error; Image analysis; Image recognition; Pixel; Production; Shape; Text recognition; Typesetting;
Journal_Title :
Image Processing, IEEE Transactions on