Quantifying scribal behavior : a novel approach to digital paleography
We propose a novel approach for analyzing scribal behavior quantitatively using information about the handwriting of characters. To implement this approach, we develop a computational framework that recovers this information and decomposes the characters into primitives (called strokes) to create a hierarchically structured representation. We then propose a number of intuitive metrics quantifying various facets of scribal behavior, which are derived from the recovered information and character structure. We further propose the use of techniques modeling the generation of handwriting to directly study the changes in writing behavior. We then present a case study in which we use our framework and metrics to analyze the development of four major Indic scripts. We show that our framework and metrics coupled with appropriate statistical methods can provide great insight into scribal behavior by discovering speciïŹc trends and phenomena with quantitative methods. We also illustrate the use of handwriting modeling techniques in this context to study the divergence of the Brahmi script into two daughter scripts. We conduct a user study with domain experts to evaluate our framework and salient results from the case
Sampath, Vinodh Rajan
Paleography ; Palaeography ; Digital paleography ; Digital palaeography ; Manuscript studies ; Digital humanities ; Quantitative paleography ; Quantitative palaeography ; Quantitative analysis ; Scripts ; Writing systems ; Analysis of writing systems ; Analysis of scripts ; Z105.S2 ; Paleography--Data processing ; Indus script--History--Data processing ; Brahmi alphabet--History--Data processing
Quantifying scribal behavior : a novel approach to digital paleography. We propose a novel approach for analyzing scribal behavior quantitatively using information about the handwriting of characters. To implement this approach, we develop a computational framework that recovers this information and decomposes the characters into primitives (called strokes) to create a hierarchically structured representation. We then propose a number of intuitive metrics quantifying various facets of scribal behavior, which are derived from the recovered information and character structure. We further propose the use of techniques modeling the generation of handwriting to directly study the changes in writing behavior. We then present a case study in which we use our framework and metrics to analyze the development of four major Indic scripts. We show that our framework and metrics coupled with appropriate statistical methods can provide great insight into scribal behavior by discovering speciïŹc trends and phenomena with quantitative methods. We also illustrate the use of handwriting modeling techniques in this context to study the divergence of the Brahmi script into two daughter scripts. We conduct a user study with domain experts to evaluate our framework and salient results from the case
scribal behavior novel digital propose_novel analyze scribal behavior quantitatively use information character implement develop computational framework recovers information decompose character primitive call stroke create hierarchically structure representation propose number intuitive metric quantify various facet scribal behavior derive recovered information character structure propose use technique model generation directly study change write behavior present case_study use framework metric analyze development four_major script show framework metric couple appropriate statistical_method provide great_insight scribal behavior discover trend phenomena quantitative_method also_illustrate use model technique context study divergence script daughter script conduct user study domain expert evaluate framework salient case