Automated Transcription of Historical Encrypted Manuscripts

Abstract

This paper deals with historical encrypted manuscripts and introduces an automated method for the detection and transcription of ciphertext symbols for subsequent cryptanalysis. Our database contains documents used in the past by aristocratic families living in the territory of Slovakia. They are encrypted using a nomenclator which is a specific type of substitution cipher. In our case, the nomenclator uses digits as ciphertext symbols. We have proposed a method for the detection, classification, and transcription of handwritten digits from the original documents. Our method is based on Mask R-CNN which is a deep convolutional neural network for instance segmentation. Mask R-CNN was trained on a manually collected database of digit annotations. We employ a specific strategy where the input image is first divided into small blocks. The image blocks are then passed to Mask R-CNN to obtain detections. This way we avoid problems related to the detection of a large number of small dense objects in a high-resolution image. Experiments have shown promising detection performance for all digit types with minimum false detections.

Encrypted Documents and Cipher Keys From the 18th and 19th Century in the Archives of Aristocratic Families in Slovakia

“…Automated image processing needs to take all these factors into consideration. Antal and Marák (2022) proposed an automated software system for historical handwritten digit detection, recognition, and transcription based on deep learning. This way, a large number of historical documents can be analyzed and solved in an automated manner.…”

“…We collected more than twelve thousand 10 polygonal annotations of digits 0-9 which are stored in well-known COCO format. More details about the annotations can be found in (Antal and Marák, 2022). Since our YOLOv7 performs digit detection on the entire image rather than on image blocks, we needed to transform geometric properties of annotations so they correspond to images of size 1280 × 1280.…”

“…Once digits are detected by YOLOv7, all bounding boxes and their corresponding class labels are passed to the automated transcription algorithm presented in (Antal and Marák, 2022) which detects lines and extracts the digits. Digits are then…”