# The Challenges of Recognizing Offline Handwritten Chinese: A Technical Review
###### Abstract
According to the criteria specified in the National Standard Simplified Chinese Character Set of the People's Republic of China (GB2312-80), there are 6763 categories of commonly used first-level and second-level Chinese characters [5]. However, it still falls short of fulfilling the demands for Chinese information processing, and the subsequent GBK and GB18030 character sets have been supplemented to address further requirements. Since each individual character in Chinese is a different class, the number of Chinese character categories in the recognition task is enormous compared to languages such as English, where only a few dozen classes of letters need to be identified. This makes the complexity of the algorithm required to recognize Chinese higher; (2) Chinese characters have intricate structures. The structure can be divided into upper and lower, left and right,  
Figure 1: Classification of Chinese recognition. The green rectangles from left to right depict the research directions of this paper from broad to specific. The orange rectangles represent relevant research directions but are not described in detail in this paper. The light blue area is the main work of this paper. semi-enveloped, and mosaic structures. The average number of strokes in traditional and simplified Chinese characters is 16 and 11, respectively, and the recognition rate is reduced due to excessive strokes. (3) There are many similar Chinese characters. These characters almost have the same spatial structure and have comparable stroke patterns, such as \"\(\square\)\" and \"\(\square\)\", \"\(\square\)\", \"\(\square\)\" and \"\(\square\)\", \"\(\square\)\", \"\(\square\)\", etc. The recognition of similar characters in the feature extraction process will have high requirements for the algorithm. (4) Different people have distinct writing styles. The handwriting of various persons varies widely, and even the script of the same person may differ in different states. At the same time, the strokes of some Chinese characters are easily deformed in writing, which will significantly increase the difficulty of recognition. Based on these problems, although offline handwritten Chinese recognition has been studied for decades, the recognition effect still does not reach people's expectations. It is still a very challenging pattern recognition problem. This paper will review the offline handwritten Chinese recognition technology to summarize and analyze the latest academic and technical progress. By searching for handwritten character recognition-related reviews, we found that these papers outline recognition methods for different languages separately and do not systematically describe the recognition of Chinese, e.g., literature [6; 7; 8]. In 2016, Ref. [9] provided a detailed analysis and summary of handwritten Chinese recognition methods. However, unfortunately, it was written in Chinese seven years ago and could not summarize the latest methodological techniques. After this paper, finding another summary article on offline handwritten Chinese recognition is difficult. Therefore, this paper reviews the recognition techniques for offline HCC and offline HCT, summarizes and analyzes the latest academic progress in this field since 2016, composes the main research issues, and suggests future works for the challenges that currently face handwritten Chinese recognition.