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The study derived seven descriptors from the pixel matrices of both the uppercase and lowercase forms of the 26 letters in the English alphabet in the regular and italic versions of the most commonly used font, Times New Roman. A factor analysis of the seven descriptors showed that a two-factor solution of letter width and height explained 76.6% of the variance. Legibility threshold of the 26 letters in the regular and italic Times Roman font and in two-case forms were collected to specify effects of letter width and height. 20 university students, 10 women and 10 men, with a mean age of 24.1 yr. (SD = 1.6) participated. They identified letters displayed initially on a PC screen at a minimum font size and enlarged gradually until the participant correctly recognized the letter. Analysis showed letters of greater width or height were more legible than those of smaller width or height. Given an oblique effect, letters in the italic Times Roman font had significantly greater width but were less legible than those in the regular font.

A novel algorithm for font recognition on a single unknown Chinese character, independent of the identity of the character, is proposed in this paper. We employ a wavelet transform on the character image and extract wavelet features from the transformed image. After a Box-Cox transformation and LDA (Linear Discriminant Analysis) process, the discriminating features for font recognition are extracted and classified through a MQDF (Modified Quadric Distance Function) classifier with only one prototype for each font class. Our experiments show that our algorithm can achieve a recognition rate of 90.28 percent on a single unknown character and 99.01 percent if five characters are used for font recognition. Compared with existing methods, all of which are based on a text block, our method can provide a higher recognition rate and is more flexible and robust, since it is based on a single unknown character. Additionally, our method demonstrates that it is possible to extract subtle yet discriminative signals embedded in a much larger noisy background. Index Terms--Font recognition, character independent, single character, wavelet features, LDA, MQDF.

The benefits of Identifont, an online font library, to library users are analyzed.

Effects of font design and electronic display parameters upon text legibility were determined using a threshold size method. Participants' visual acuity (inverse of the minimum detection size, representing the threshold legibility for each condition) was measured using upper- and lowercase letters and lowercase words in combinations of 6 fonts, 3 font-smoothing modes, 4 font sizes, 10 pixel heights, and 4 stroke widths. Individual lowercase letters were 10% to 20% more legible than lowercase words (i.e., lowercase words must be 10%-20% larger to have the same threshold legibility). This letter superiority effect suggests that individual letters play a large role and word shape plays a smaller role, if any, in word identification at threshold. Pixel height, font, stroke width, and font smoothing had significant main effects on threshold legibility. Optimal legibility was attained at 9 pixels (10 points). Verdana and Arial were the most legible fonts: Times New Roman and Franklin were least legible. Subpixel rendering (ClearType[TM]) improved threshold legibility for some fonts and, in combination with Verdana, was the most legible condition. Increased stroke width (bold) improved threshold legibility but only at the thinnest width tested. Potential applications of this research include optimization of font design for legibility and readability.

Font follies It's that time of year again. Regular readers of this column know that April is the saintlike compassion and focus more intently on the foolishness that pervades the […]