{"url":"/method/intgaussder","slug":"intgaussder","name":"intgaussder","full_name":"integrated Gaussian derivative kernel","full_name_withheld":false,"description_markdown":"Integrated Gaussian derivative kernels are obtained by integrating the continuous Gaussian derivative kernels over each pixel support region. In this way, some of the severe artefacts of sampling the Gaussian derivative kernels at too fine scales can be reduced.","description_state":"present","introduced_year":null,"introduced_by":{"title":"Discrete approximations of Gaussian smoothing and Gaussian derivatives","paper":"/paper/discrete-approximations-of-gaussian-smoothing","first_author":"Tony Lindeberg","n_authors":1,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/discrete-approximations-of-gaussian-smoothing"},"source":{"url":"https://arxiv.org/abs/2311.11317v7","title":"Discrete approximations of Gaussian smoothing and Gaussian derivatives","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Sequential","area_id":"sequential","collection":"Multi-scale analysis","url":"/methods/category/multi-scale-analysis","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":1,"papers_newest_first":[{"paper":"/paper/discrete-approximations-of-gaussian-smoothing","title":"Discrete approximations of Gaussian smoothing and Gaussian derivatives","date":"2023-11-19","arxiv_id":"2311.11317","n_code_links":1,"syntology":null}],"papers_shown":1,"tasks":[],"tasks_shown":0,"n_tasks":0,"usage_by_year":[{"year":"2023","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/intgaussder"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}