(B–G) Each graph shown separately where red dots show nodes (endpoints and intersections).
Red dots denote graph breakpoints of the connected writing. (A) Binarized pen strokes in gray, pixel-wide skeleton overlaid in mblack. The word “csafe” taken from a processed document. Using a subset of the CVL handwriting database, they applied their clustering method on a set of documents with known origins to perform a writership analysis. She said their clustering algorithm relies on a novel distance measure and a mean calculation they developed and designed specifically for graphs that represent handwriting. “This allows graphs with similar, but not identical, graphical structures to be placed in the same group.” “We developed a dynamic and flexible K-means-based clustering method that is tolerant to incidental pen strokes,” said Carriquiry. Alicia Carriquiry, director of CSAFE and a co-author of the study, said they developed an approach that allowed them to control the number of groupings, each of which will hold graphs that may not be identical in connectivity but have a similar dominating structure. Next, the graphs were grouped using measures based on the similarity of structural attributes. These graph structures will be the basis for evaluating the structural styles of a writer. The writing was segmented into small graphical structures, called graphs, using CSAFE’s publicly available handwriter R algorithm package. The study, published in Statistical Analysis and Data Mining, scanned and analyzed handwritten documents from a variety of writers in the Computer Vision Lab (CVL) database.
Recently published research from Center for Statistics and Applications in Forensic Evidence (CSAFE) researchers details a new approach for analyzing the shapes made in handwriting to determine their source, a development that one day may be useful in forensic practice. Three graph whose assignment will contribute to characterizing a writer’s style.D is deterministic group assignment.C is cluster group assignment.
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