{"id":"W2071347067","doi":"10.1142/s0219467801000359","title":"TWO ALGORITHMS FOR COMPUTING THE EUCLIDEAN DISTANCE TRANSFORM","year":2001,"lang":"en","type":"article","venue":"International Journal of Image and Graphics","topic":"Digital Image Processing Techniques","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Algorithm; Euclidean distance; Pixel; Feature (linguistics); Metric (unit); Euclidean geometry; Computer science; Distance transform; Binary number; Image processing; Mathematics; Image (mathematics); Artificial intelligence; Arithmetic","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001428968,0.001618463,0.001701792,0.002865486,0.0008759029,0.002635238,0.00284642,0.002010995,0.007389214],"category_scores_gemma":[0.01024217,0.0008768627,0.001325282,0.002786666,0.001312715,0.005248276,0.002729573,0.00267026,0.004975447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001176603,"about_ca_system_score_gemma":0.002322121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002428825,"about_ca_topic_score_gemma":0.003448756,"domain_scores_codex":[0.9965479,0.0004322562,0.0003161584,0.000735899,0.001626044,0.0003418991],"domain_scores_gemma":[0.9972638,0.0006862268,0.0002068608,0.0006275388,0.001080038,0.0001354922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000331874,0.0001803858,0.000533864,0.0002481647,0.0000572311,0.0001004535,0.0001199278,0.03839707,0.009990929,0.09731311,0.01290371,0.8398232],"study_design_scores_gemma":[0.0004116713,0.0005085038,0.001386859,0.0000937291,0.00009048118,0.001424097,0.0002176691,0.7110367,0.04769943,0.1628637,0.07402254,0.0002446435],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001281718,0.0002302494,0.9963506,0.0001177396,0.0001307731,0.00004768421,0.00006092839,0.0006120488,0.001168263],"genre_scores_gemma":[0.018192,0.0003048581,0.9785218,0.00006195813,0.0001186646,0.0002147442,0.0003679024,0.0001444703,0.00207359],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007389214,"threshold_uncertainty_score":0.02471942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02054997366559403,"score_gpt":0.3258167522426751,"score_spread":0.3052667785770811,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}