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US08244038B2 Text vectorization using OCR and stroke structure modeling 失效
使用OCR和笔画结构建模的文本向量化

Text vectorization using OCR and stroke structure modeling
Abstract:
Systems and methods are described that facilitate dominant point detection for text in a scanned document. The dominant points are classified as “major” (e.g., structural) and “minor” (e.g., serif). A set of rules or parameters for each character is determined off-line. During the text vectorization, OCR is performed and the rules (parameters) associated with the recognized character are selected. Both major and minor dominant points are detected as a maximization process with the parameter set. For minor dominant points, additional processes are optionally employed.
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