Optical font recognition using typographical features

Abstract

Abstract-A new statistical approach based on global typographical features is proposed to the widely neglected problem of font recognition. It aims at the identification of the typeface, weight, slope and size of the text from an image block without any knowledge of the content of that text. The recognition is based on a multivariate Bayesian classifier and operates on a given set of known fonts. The effectiveness of the adopted approach has been experimented on a set of 280 fonts. Font recognition accuracies of about 97 percent were reached on high-quality images. In addition, rates higher than 99.9 percent were obtained for weight and slope detection. Experiments have also shown the system robustness to document language and text content and its sensitivity to text length.

Typography and Its Significant to Memorizing a Logo

“…Gabriele [11] and Zramdini & Ingold [12] studied the physical aspect of typography and found that it has an impact to the mind, which is also agreed by Rojas & Roast [13].…”

Adaptive and Interactive Approaches to Document Analysis

“…The font classifier is then applied first to a test field, and its decision is used to select the appropriate character classifier [40,41,42,43]. The same idea can be applied to writer identification [44].…”

Multifont classification using typographical attributes

“…As shown in Figure 4, text line images are composed of three typographical zones: the ascender, the x height and the descender zones, which are delimited by four virtual horizontal lines, ascender, x height, base and descender lines [3]. The lowercases with ascenders that extend above the x height line are b, d, f, h, k, l, i, and t. They occupy the ascender and the x height zones.…”

“…From the vertical projection profile of a word image after the correction of skew angle, the typographical structure can be estimated. The analysis of the vertical projection profile shows that a word image has one of four types [4], Type I: The presence of all three zones, Type II: The presence of the ascender and the x height zones,…”

“…marked in Figure 5c) are discarded. The slope detection algorithm [3] is used to detect the blobs with a slant side. It is observed from the horizontal projection profile of a candidate blob that the vertical stroke is characterized by an upright stem while the one with a slant side is characterized by a rounded peak.…”