Computer Vision And Deep Learning Tools For The Automatic Processing Of Wasan Documents

"Wasan" is a type of mathematical texts unique from Japan developed during the Edo period (1603-1867). These ancient documents present a wealth of knowledge and are of great cultural and historical importance. In this paper we present a fully automatic algorithm to locate a landmark element within Wasan documents. Specifically, we use classical computer vision techniques as well as deep learning tools in order to locate one particular kanji character called the "ima" kanji. Even though the problem is challenging due to the low image quality of manually scanned ancient documents and the complexity of handwritten kanji detection and recognition, our pipeline including noise reduction, orientation correction, candidate kanji region detection and kanji classification achieves a 93% success rate. Experiments run on a dataset with 373 images are presented.