Offline Chinese handwriting recognition (OCHR) is a typically difficult pattern recognition problem. Many authors have presented various approaches to recognizing its different aspects. We present a survey and an assessment of relevant papers appearing in recent publications of relevant conferences and journals, including those appearing in ICDAR, SDIUT, IWFHR, ICPR, PAMI, PR, PRL, SPIE-DRR, and IJDAR. The methods are assessed in the sense that we document their technical approaches, strengths, and weaknesses, as well as the data sets on which they were reportedly tested and on which results were generated. We also identify a list of technology gaps with respect to Chinese handwriting recognition and identify technical approaches that show promise in these areas as well as identify the leading researchers for the applicable topics, discussing difficulties associated with any given approach.

Over the last century forensic document science has developed progressively more sophisticated pattern recognition methodologies for ascertaining the authorship of disputed documents. We present a writer verification method and an evaluation of its performance on historical documents with known and unknown writers. The questioned document is compared against handwriting samples of Herman Melville, a 19th century American author who has been hypothesized to be the writer as well as against samples crafted by several writers from the same time period. The comparison led to a high confidence result to the questioned document's writership, as well as gives evidence for the validity of the writer verification method in the context of historical documents. Such methodology can be applied to many such questioned historical documents, both in literary and legal fields.

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