Automatic measure of visual similarity between fonts
作者： R. David Arnold , Eric Muller , Judy S. Lee , Zhihong Ding , Timothy Wojtaszek
DOI:
关键词: Visual descriptors 、 Mathematics 、 Measure (mathematics) 、 Artificial intelligence 、 Pattern recognition 、 Set (abstract data type) 、 Function (mathematics) 、 Character (computing) 、 Computer vision 、 Font 、 Image (mathematics) 、 Similarity (geometry)
摘要: The visual similarity between fonts is determined using descriptors of character images in the fonts. A model used to generate may include a set letterforms, keypoint locations on each letterform, and detail shapes at zero, one, or more areas letterform. In some instances, also forth one geometric measurements. Based model, descriptor be generated for image from font by identifying letterform image, shape any image. Additionally, measurement defined model. two as function differences pairs that correspond with same
lens.org 参考文章(11)
Sampo Juhani Kaasila, Jitendra Kumar Bansal Bhawan Bansal, Anand Vijay, Analyzing font similarity for presentation ,(2013)
Joshua J. Estelle, Alexander Jay Cuthbert, Presenting translations of text depicted in images ,(2013)
Philip Andrew Chou, Leslie T. Niles, Gary E. Kopec, Automatic training of character templates using a transcription and a two-dimensional image source model ,(1995)
Mark D. Seaman, Dan S. Johnson, Noise tolerant optical character recognition system ,(1991)
Thomas B. Hawkins, Allan W. Ristow, Method for data compression of digital data to produce a scaleable font database ,(1994)
Yaakov Navon, Boaz Ophir, Method for extracting text from a compound digital image ,(2007)
Akira Kijima, Hideki Kawabata, Image inspecting apparatus and image inspecting program ,(2014)
Hiroshi Nakamura, Method and apparatus for reading barcode information ,(2011)
Dennis G. Nicholson, Reconstructing high-fidelity electronic documents from images via generation of synthetic fonts ,(2005)