{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/stroke-extraction-of-chinese-character-based","title":"Stroke Extraction of Chinese Character Based on Deep Structure Deformable Image Registration","arxiv_id":"2307.04341","date":"2023-07-10","proceeding":null,"authors":["Meng Li","Yahan Yu","Yi Yang","Guanghao Ren","Jian Wang"],"abstract":"Stroke extraction of Chinese characters plays an important role in the field of character recognition and generation. The most existing character stroke extraction methods focus on image morphological features. These methods usually lead to errors of cross strokes extraction and stroke matching due to rarely using stroke semantics and prior information. In this paper, we propose a deep learning-based character stroke extraction method that takes semantic features and prior information of strokes into consideration. This method consists of three parts: image registration-based stroke registration that establishes the rough registration of the reference strokes and the target as prior information; image semantic segmentation-based stroke segmentation that preliminarily separates target strokes into seven categories; and high-precision extraction of single strokes. In the stroke registration, we propose a structure deformable image registration network to achieve structure-deformable transformation while maintaining the stable morphology of single strokes for character images with complex structures. In order to verify the effectiveness of the method, we construct two datasets respectively for calligraphy characters and regular handwriting characters. The experimental results show that our method strongly outperforms the baselines. Code is available at https://github.com/MengLi-l1/StrokeExtraction.","url_abs":"https://arxiv.org/abs/2307.04341v1","url_pdf":"https://arxiv.org/pdf/2307.04341v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"stroke-extraction-of-chinese-character-based","repo_url":"https://github.com/mengli-l1/strokeextraction","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"image-registration","task_name":"Image Registration"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[{"method_slug":"focus","method_name":"Focus"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2307.04341","atlas_url":"https://app.syntology.ai/?focus=2307.04341","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.04341"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"deterministic:regex_extraction","url":"https://github.com/MengLi-l1/StrokeExtraction","reach":null}],"summary":{"ran":3,"unverified":3},"by_repo_kind":{"official":{"samples":6,"ran":3,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":6,"samples":[{"code_sha256_prefix":"e35eccc70fc227f1","entry":"CharRecognise","repo":"MengLi-l1/StrokeExtraction","repo_kind":"official","path":"model/model_of_SDNet.py","file_url":"https://github.com/MengLi-l1/StrokeExtraction/blob/HEAD/model/model_of_SDNet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"e35eccc70fc227f1"}},{"code_sha256_prefix":"502d49689f633efb","entry":"SpatialTransformer","repo":"MengLi-l1/StrokeExtraction","repo_kind":"official","path":"model/model_of_SDNet.py","file_url":"https://github.com/MengLi-l1/StrokeExtraction/blob/HEAD/model/model_of_SDNet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"502d49689f633efb"}},{"code_sha256_prefix":"260713377ec930c1","entry":"conv_block","repo":"MengLi-l1/StrokeExtraction","repo_kind":"official","path":"model/model_of_SDNet.py","file_url":"https://github.com/MengLi-l1/StrokeExtraction/blob/HEAD/model/model_of_SDNet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"260713377ec930c1"}},{"code_sha256_prefix":"18d885993b62c339","entry":"SDNet","repo":"MengLi-l1/StrokeExtraction","repo_kind":"official","path":"model/model_of_SDNet.py","file_url":"https://github.com/MengLi-l1/StrokeExtraction/blob/HEAD/model/model_of_SDNet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"18d885993b62c339"}},{"code_sha256_prefix":"f1070649a967c085","entry":"UNetWithFeature","repo":"MengLi-l1/StrokeExtraction","repo_kind":"official","path":"model/model_of_SDNet.py","file_url":"https://github.com/MengLi-l1/StrokeExtraction/blob/HEAD/model/model_of_SDNet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f1070649a967c085"}},{"code_sha256_prefix":"096345e22a257ebf","entry":"inception_block","repo":"MengLi-l1/StrokeExtraction","repo_kind":"official","path":"model/model_of_SDNet.py","file_url":"https://github.com/MengLi-l1/StrokeExtraction/blob/HEAD/model/model_of_SDNet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"096345e22a257ebf"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}