## 4 Evaluations
### Fully Automated Processing of 19 th Century Novels
#### 4.2.2 Interpretations  
ABBY struggled noticeably with substantially soiled pages, recognizing lines in regions showing dirt or bleed-through on a regular basis, resulting in gibberish OCR output. OCR4 all showed only a few segmentation errors, with the main problem being left out page numbers, which happened due to a heuristic in the OCRopus 1 line segmentation script that ignores lines that contain less than three CCs. Table 4 lists the most common OCR errors. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**ABBYY**} & \multicolumn{3}{c}{**OCR4 all**} \\ \hline
**GT** & **OCR** & **CNT** & **\%** & **GT** & **OCR** & **CNT** & **\%** \\ \hline \multirow{3}{*}{\(\backsim\)} & & 64 & 2.6 & \multirow{3}{*}{\(\backsim\)} & 63 & 11.9 \\  & & 57 & 2.3 & n & u & 14 & 2.7 \\ \cline{1-1} \cline{5-8} \multirow{3}{*}{s} & \(\mathsf{S}\) & 57 & 2.3 & f & s & 12 & 2.3 \\  & \({}^{\prime}\) & 50 & 2.0 & i & l & 12 & 2.3 \\ e & c & 40 & 1.6 & r & t & 12 & 2.3 \\ \hline \multicolumn{8}{c}{Remaining} & 89.2 & \multicolumn{3}{c}{Remaining} & 78.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The five most common confusions over all ten books for ABBYY Finereader and OCR4 all, consisting of the GT, the prediction (OCR), the Counted Number of Occurrences (CNT) and the percent contribution (%) of a given confusion to the overall number of errors. Whitespaces are shown as \(\backsim\) and empty cells denote no prediction. Please note that the absolute occurrences of the top error are almost identical for both approaches, but the percentages differ considerably due to the vastly smaller number of errors achieved by OCR4 all. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Book** & **ABBYY** & **OCR4 all** & **ErrRed.** & **Impr.** \\ \hline F1781 & 2.9 & 0.60 & 79.3 & 4.8 \\ F1803 & 27 & 4.89 & 81.9 & 5.5 \\ F1810 & 3.8 & 0.61 & 84.0 & 6.2 \\ F1818 & 10 & 1.35 & 86.6 & 7.5 \\ F1826 & 1.1 & 0.06 & 94.4 & 18 \\ F1848 & 0.93 & 0.20 & 78.5 & 4.7 \\ F1851 & 1.0 & 0.16 & 84.0 & 6.3 \\ F1855 & 4.0 & 0.33 & 91.8 & 12 \\ F1865 & 1.6 & 0.18 & 88.8 & 8.9 \\ F1870 & 0.48 & 0.13 & 72.9 & 3.7 \\ \hline
**Avg.** & **5.3** & **0.85** & **84.2** & **7.8** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: CERs achieved by ABBYY Finereader and OCR4 all when being applied fully automatically to different books. The final two columns indicate the percent error reduction _ErrRed._ and the improvement factor _Impr._ yielded by OCR4 all over ABBYY. Furthermore, we provide the average _Avg._ over all books for each value. First of all, it was apparent that the error distribution of the results produced by OCR4 all was more top heavy, with the top five making up for almost 22% of the total errors, compared to the one of ABBYY (close to 11%). However, the distributions were actually quite similar to each other, apart from the top error of OCR4 all, namely the deletion of whitespaces, which was responsible for almost 12% of the errors alone. Interestingly, while insertions and deletions of whitespaces represented the top two errors for ABBYY and OCR4 all also failed to predict them on a regular basis, insertions of whitespaces did not occur in the top ten of OCR4 all at all. The remainder of the most frequent OCR4 all errors looked as expected, containing well known errors like the confusion of similar looking (at least in 19 th Century Fraktur script) characters like \(n\) and \(u\),\(f\) and \(s\) (originally predicted as the long s and then regularized), or \(c\) and \(e\), as well as the insertions and deletions of tiny elements like commata, sometimes also as part of quotation marks. Furthermore, some of the aforementioned typical OCR errors like the confusions of \(e\) and \(c\) and \(s\) and \(S\) still were surprising since one would expect the powerful dictionary and language modeling capabilities of ABBYY to deal with these errors quite comfortably.