Campus Units
Statistics, Center for Statistics and Applications in Forensic Evidence (CSAFE)"
Document Type
Article
Publication Version
Published Version
Publication Date
11-24-2020
Journal or Book Title
Statistical Analysis and Data Mining: The ASA Data Science Journal
Volume
14
Issue
1
First Page
41
Last Page
60
DOI
10.1002/sam.11488
Abstract
Handwritten documents can be characterized by their content or by the shape of the written characters. We focus on the problem of comparing a person's handwriting to a document of unknown provenance using the shape of the writing, as is done in forensic applications. To do so, we first propose a method for processing scanned handwritten documents to decompose the writing into small graphical structures, often corresponding to letters. We then introduce a measure of distance between two such structures that is inspired by the graph edit distance, and a measure of center for a collection of the graphs. These measurements are the basis for an outlier tolerant K‐means algorithm to cluster the graphs based on structural attributes, thus creating a template for sorting new documents. Finally, we present a Bayesian hierarchical model to capture the propensity of a writer for producing graphs that are assigned to certain clusters. We illustrate the methods using documents from the Computer Vision Lab dataset. We show results of the identification task under the cluster assignments and compare to the same modeling, but with a less flexible grouping method that is not tolerant of incidental strokes or outliers.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright Owner
The Authors
Copyright Date
2020
Language
en
File Format
application/pdf
Recommended Citation
Crawford, Amy M.; Berry, Nicholas S.; and Carriquiry, Alicia L., "A clustering method for graphical handwriting components and statistical writership analysis" (2020). CSAFE Publications. 77.
https://lib.dr.iastate.edu/csafe_pubs/77
Comments
This article is published as Crawford, Amy M., Nicholas S. Berry, and Alicia L. Carriquiry. "A clustering method for graphical handwriting components and statistical writership analysis." Statistical Analysis and Data Mining: The ASA Data Science Journal 14, no. 1 (2021): 41-60. Posted with permission of CSAFE.