{"id":18556646,"url":"https://github.com/ahmdtaha/textureclassification_filterbank","last_synced_at":"2025-08-22T16:04:31.126Z","repository":{"id":98612509,"uuid":"51297424","full_name":"ahmdtaha/TextureClassification_FilterBank","owner":"ahmdtaha","description":"This repos provides an MATLAB code implementation for the Statistical Approach to Texture Classification from Single Images paper by Varma et. al.","archived":false,"fork":false,"pushed_at":"2018-01-30T18:57:13.000Z","size":17,"stargazers_count":12,"open_issues_count":1,"forks_count":6,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-10T16:53:07.873Z","etag":null,"topics":["classification-toolbox","columbia-utrecht-dataset","matlab","texture-classification","varma"],"latest_commit_sha":null,"homepage":"","language":"Matlab","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-2-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ahmdtaha.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-02-08T12:46:22.000Z","updated_at":"2024-10-16T15:36:45.000Z","dependencies_parsed_at":"2023-11-22T13:30:30.756Z","dependency_job_id":null,"html_url":"https://github.com/ahmdtaha/TextureClassification_FilterBank","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahmdtaha%2FTextureClassification_FilterBank","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahmdtaha%2FTextureClassification_FilterBank/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahmdtaha%2FTextureClassification_FilterBank/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahmdtaha%2FTextureClassification_FilterBank/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ahmdtaha","download_url":"https://codeload.github.com/ahmdtaha/TextureClassification_FilterBank/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ahmdtaha%2FTextureClassification_FilterBank/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":259172955,"owners_count":22816556,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["classification-toolbox","columbia-utrecht-dataset","matlab","texture-classification","varma"],"created_at":"2024-11-06T21:32:35.761Z","updated_at":"2025-06-11T00:04:55.280Z","avatar_url":"https://github.com/ahmdtaha.png","language":"Matlab","funding_links":[],"categories":[],"sub_categories":[],"readme":"\nStatistical Approach to Texture Classification from Single Images\n-----------------------------------------------------------------\n\nThis repos provides an implementation for the \"[Statistical Approach to Texture Classification from Single Images](http://www.robots.ox.ac.uk/~vgg/publications/2005/Varma05/)\" paper by Varma et. al.\n\nThe filters (RFS, LM, S) used in this repos are from [this link](http://www.robots.ox.ac.uk/~vgg/research/texclass/filters.html)\n\nIt is not documented yet. Since I know that it will take me some time to write the documentation, I decided to provide this initial version of the code. There is a lot of work that can help make this code better. So any contributions will be welcomed.\n\nLibraries\n---------\nTo be able to run this code, you need to download the following libraries\n - [VLFeat open source library](http://www.vlfeat.org/)\n - [Classification toolbox for MATLAB, by Milano Chemometrics and QSAR Research Group](http://michem.disat.unimib.it/chm/download/softwares/help_classification/web.htm). \n \n VLFeat Library is used to calculate K-means (vl_kmeans) and the distance between new  nodes and pre-computed centroids (vl_alldist).\n Classification toolbox is used to find the nearest neighbor during the classification phase.\n\nSetup\n-----\n\n 1. Download the code.\n 2. Download the [Classification toolbox for \n 3. MATLAB, by Milano Chemometrics and QSAR Research Group](http://michem.disat.unimib.it/chm/download/softwares/help_classification/web.htm). \n 3. Update the knn_calc_dist.m file with the file inside this repos, to support chi-square distance\n 4. Update the \"rootpath\" variable in demo_curet.m to point to Columbia-Utrecht dataset folder on your machine.\n 5. Run demo_curet.m to test the performance over Columbia-Utrecht dataset.\n\nI will try to update the documentation incrementally to provide more instructions to make using this code easier.\n\nContributor list\n----------------\n1. [Ahmed Taha](http://ahmed-taha.com/)\n2. [Aleksandrs Ecins](http://www.umiacs.umd.edu/~aecins/)\n\n## License\nTextureClassification_FilterBank is released under the BSD 2-Clause license. The code is released for unrestricted use.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahmdtaha%2Ftextureclassification_filterbank","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fahmdtaha%2Ftextureclassification_filterbank","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahmdtaha%2Ftextureclassification_filterbank/lists"}