Effect of Text/Non-text Classification for Ink Search Employing String Recognition
Tomohisa Matsushita, Cheng Cheng, Yūjirō Murata, Bilan Zhu, Masaki Nakagawa · 2012
This paper presents the effect of text/non-text classification for ink search which employs string recognition. Pen or touch interfaces provides the benefit that users can write text and draw figures without changing the device or mode, but line drawings are troublesome for ink search. We propose the insertion of text/non-text classification before ink search and show its effect. For ink search, we employ our own engine to search keywords in the candidate lattice prepared by on-line handwritten Japanese text recognition, since this method produces higher search rate for Japanese text in digital ink than word spotting without ink recognition.