Document Type
Conference Proceeding
Publication Date
9-2019
Publication Title
International Conference on Document Analysis and Recognition
Abstract
Alignment tasks generally seek to establish a spatial correspondence between two versions of a text, for example between a set of manuscript images and their transcript. This paper examines a different form of alignment problem, namely pixel-scale alignment between two renditions of a handwritten word or phrase. Using loopy inkball graph models, the proposed technique finds spatial correspondences between two text images such that similar parts map to each other. The method has applications to word spotting and signature verification, and can provide analytical tools for the study of handwriting variation.
Keywords
alignment, inkball, handwriting, pattern recognition
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Rights
“Licensed to Smith College and distributed CC-BY under the Smith College Faculty Open Access Policy.”
Recommended Citation
Howe, Nicholas and Chung, Ji Won, "Symmetric Inkball Alignment with Loopy Models" (2019). Computer Science: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/csc_facpubs/137
Comments
Author’s submitted manuscript.