Abstract

“Wasan” is the collective name given to a set of mathematical texts written in Japan in the Edo period (1603–1867). These documents represent a unique type of mathematics and amalgamate the mathematical knowledge of a time and place where major advances where reached. Due to these facts, Wasan documents are considered to be of great historical and cultural significance. This paper presents a fully automatic algorithmic process to first detect the kanji characters in Wasan documents and subsequently classify them using deep learning networks. We pay special attention to the results concerning one particular kanji character, the “ima” kanji, as it is of special importance for the interpretation of Wasan documents. As our database is made up of manual scans of real historical documents, it presents scanning artifacts in the form of image noise and page misalignment. First, we use two preprocessing steps to ameliorate these artifacts. Then we use three different blob detector algorithms to determine what parts of each image belong to kanji Characters. Finally, we use five deep learning networks to classify the detected kanji. All the steps of the pipeline are thoroughly evaluated, and several options are compared for the kanji detection and classification steps. As ancient kanji database are rare and often include relatively few images, we explore the possibility of using modern kanji databases for kanji classification. Experiments are run on a dataset containing 100 Wasan book pages. We compare the performance of three blob detector algorithms for kanji detection obtaining 79.60% success rate with 7.88% false positive detections. Furthermore, we study the performance of five well-known deep learning networks and obtain 99.75% classification accuracy for modern kanji and 90.4% for classical kanji. Finally, our full pipeline obtains 95% correct detection and classification of the “ima” kanji with 3% False positives.

Highlights

  • As it was impractical to run all parameter combinations with the full database, five Wasan images were used for the fine-tuning process, several parameter combinations where considered and the results for each of them was visually and automatically checked. minσ and maxσ are related to the size of the blobs detected, and we obtained the best results with values minσ ∈ (35, 45), maxσ ∈ (45, 50), the numσ parameter related to the step size when exploring the parameter space and was set to 5

  • 4.3. “ima” Kanji Detection In Section 3.3, we presented a detailed study of how our algorithmic process can be used to locate an important structural element of Wasan Documents, the “ima” kanji that marks the location of the geometric problem diagram and is the first character in the textual description

  • The process described in this study is the first step in the construction of a database of Wasan documents

Read more

Summary

Introduction

The general public (samurai, merchants, farmers) learned a type of mathematics developed for people to enjoy, and Wasan documents have been used by Japanese citizens as a mathematics study tool or as a mental training hobby ever since [1,2]. These mathematics were studied from a completely different perspective from the mathematics learned in the West at the time and, in particular, did not have application goals [3]. These masters studied academic content at a level comparable to Western mathematics of the same period

Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call