Importance and challenges of handwriting recognition with the implementation of machine learning techniques: a survey

Ancient manuscripts store historical, literary, cultural, and geographical information. Therefore, the automatic analysis of manuscripts is of great interest in heritage culture and history preservation. Different approaches to handwriting recognition using images have been applied to analyze manuscripts. However, reliable handwriting recognition is a considerable challenge due to different factors related to the writer, the design, the script, the manuscript, and the economy. This paper presents the most relevant works in handwriting recognition using machine learning techniques. The contributions are: i) provide a review of previous research addressing handwriting recognition, ii) depict the general methodology using machine learning in handwriting recognition, iii) highlight relevant works at different levels of analysis (character, word, text line, and text block), iv) present handwriting datasets including the type of content they have, script and language, and v) present the importance and challenges in handwriting recognition. We are confident that the insights and reflections from this review will have a positive impact on the gaps for future research in handwriting recognition.