Efficient Scene Text Localization and Recognition with Local Character Refinement

An unconstrained end-to-end text localization and recognition method is presented. The method detects initial text hypothesis in a single pass by an efficient region-based method and subsequently refines the text hypothesis using a more robust local text model, which deviates from the common assumption of region-based methods that all characters are detected as connected components. Additionally, a novel feature based on character stroke area estimation is introduced. The feature is efficiently computed from a region distance map, it is invariant to scaling and rotations and allows to efficiently detect text regions regardless of what portion of text they capture. The method runs in real time and achieves state-of-the-art text localization and recognition results on the ICDAR 2013 Robust Reading dataset

A Sketch-Based Educational System for Learning Chinese Handwriting

Learning Chinese as a Second Language (CSL) is a difficult task for students in English-speaking countries due to the large symbol set and complicated writing techniques. Traditional classroom methods of teaching Chinese handwriting have major drawbacks due to human experts’ bias and the lack of assessment on writing techniques. In this work, we propose a sketch-based educational system to help CSL students learn Chinese handwriting faster and better in a novel way. Our system allows students to draw freehand symbols to answer questions, and uses sketch recognition and AI techniques to recognize, assess, and provide feedback in real time. Results have shown that the system reaches a recognition accuracy of 86% on novice learners’ inputs, higher than 95% detection rate for mistakes in writing techniques, and 80.3% F-measure on the classification between expert and novice handwriting inputs

Image and interpretation using artificial intelligence to read ancient Roman texts

The ink and stylus tablets discovered at the Roman Fort of Vindolanda are a unique resource for scholars of ancient history. However, the stylus tablets have proved particularly difficult to read. This paper describes a system that assists expert papyrologists in the interpretation of the Vindolanda writing tablets. A model-based approach is taken that relies on models of the written form of characters, and statistical modelling of language, to produce plausible interpretations of the documents. Fusion of the contributions from the language, character, and image feature models is achieved by utilizing the GRAVA agent architecture that uses Minimum Description Length as the basis for information fusion across semantic levels. A system is developed that reads in image data and outputs plausible interpretations of the Vindolanda tablets

Learner-Friendly Kanji Learning System with Radical Analysis

This paper presents a novel friendly Kanji learning system using Radical Analysis to enable foreign people and elementary school students to learn Kanji by an interesting and efficient way. This way is for characters to analyze for each radical, to divide into some parts, and to correct strokes for each divided part. Here, the Radical Analysis Database (RAD) is used for dividing characters. RAD is a database to analyze characters for each radical and divide into some parts. On the other hand, characters are corrected by using a threshold. The threshold is a judgment value in the correction and learners can set it freely by handling threshold bars put on the interface. Then, the novel system is improved so that learners can set thresholds for each divided part. Since each bar corresponds to each part, the system judges whether each part is corrected or not according to set thresholds. Hence, since learners can freely determine radicals or parts in which they want to be instructed intensively, they can practice only their radicals not good or part of the character and easily master difficult characters, too. In addition, an animation helps learners understand the order of strokes virtually. Since each stroke used in this animation is displayed with different colors, learners can also understand virtually where the same strokes are from and to at once.DOI: http://dx.doi.org/10.11591/ijere.v1i1.47