Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
536011 | Pattern Recognition Letters | 2011 | 6 Pages |
In this paper a new approach is presented for tackling the problem of identifying the author of a handwritten text. This problem is solved with a simple, yet powerful, modification of the so called ALVOT family of supervised classification algorithms with a novel differentiated-weighting scheme. Compared to other previously published approaches, the proposed method significantly reduces the number and complexity of the text-features to be extracted from the text. Also, the specific combination of line-level and word-level features used introduces an eclectic paradigm between texture-related and structure-related approaches.
► We identify a handwritten text’s author with supervised-classification techniques. ► Significantly reduced number and complexity of text-features at word and line levels. ► We use a modified ALVOT algorithm along with a novel differentiated-weighting scheme. ► Shows an eclectic paradigm between texture-related and structure-related approaches.