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ASCII art detection and recognition is an important branch of current network information processing. However, due to ASCII art's text-based organization and image-based semantic expression, traditional natural language processing (NLP) and image recognition fail to yield ideal results. This paper designs an ASCII art localization and extraction algorithm based on string distance for highly mixed text and ASCII art, aiming to segment clean ASCII art for subsequent recognition. Additionally, an evaluation standard for ASCII art extraction effectiveness is defined. Experimental results show that the proposed algorithm performs well in locating and extracting ASCII art. © 2024 IEEE.
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年份: 2024
页码: 148-152
语种: 英文
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