Least-Squares Font Metric Estimation from Images1
نویسنده
چکیده
Gary E. Kopec2 Xerox Palo Alto Research Center June 15, 1993 Abstract Character placement in digital typography is commonly defined in terms of a set of parameters (font metrics) that specify the relative locations of the local coordinate systems of adjacent characters in a line of text. The primary font metrics for horizontal letterspacing are the character set widths and sidebearings and the character pair spacing adjustments (kerning terms). A typical parameter for vertical alignment is the character depth below baseline. This paper discusses the problem of determining font metrics from measurements on images of typeset text and develops least-squares procedures for font metric estimation. When it is known 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. A novel application of font metric estimation to text image editing is discussed.
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تاریخ انتشار 1993