{"id":23463750,"url":"https://github.com/abhinav2712/rash-detector","last_synced_at":"2025-07-17T23:06:04.296Z","repository":{"id":157484602,"uuid":"633511175","full_name":"abhinav2712/Rash-Detector","owner":"abhinav2712","description":"Detection of Rashes using Image Processing in matlab","archived":false,"fork":false,"pushed_at":"2023-04-27T17:00:54.000Z","size":5,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-12T13:15:49.773Z","etag":null,"topics":["image-classification","image-processing","machine-learning","matlab","matlab-toolbox","ml"],"latest_commit_sha":null,"homepage":"","language":"MATLAB","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/abhinav2712.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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,"zenodo":null}},"created_at":"2023-04-27T16:54:35.000Z","updated_at":"2023-04-27T16:57:12.000Z","dependencies_parsed_at":null,"dependency_job_id":"020bed3e-f35a-4e7a-b2d4-805ca4022194","html_url":"https://github.com/abhinav2712/Rash-Detector","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/abhinav2712/Rash-Detector","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhinav2712%2FRash-Detector","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhinav2712%2FRash-Detector/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhinav2712%2FRash-Detector/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhinav2712%2FRash-Detector/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/abhinav2712","download_url":"https://codeload.github.com/abhinav2712/Rash-Detector/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhinav2712%2FRash-Detector/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265677305,"owners_count":23809943,"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":["image-classification","image-processing","machine-learning","matlab","matlab-toolbox","ml"],"created_at":"2024-12-24T09:16:10.186Z","updated_at":"2025-07-17T23:06:04.290Z","avatar_url":"https://github.com/abhinav2712.png","language":"MATLAB","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Rash-Detector\n\nThis code uses a colour detection technique to detect a rash given in a specific colour range of the image.\n\n## Installation\n\nClone or download the repository.\nMake sure to have MATLAB installed in your system.\n\n## Usage\n- Run the script color_detection.m in MATLAB.\n- The script reads an image file from a specified path using the imread() function.\n- The color range for each channel (red, green, and blue) is defined using the red-Range, green-Range, and blue-Range variables in the code. These ranges determine the minimum and maximum values for each color channel that are considered within the color range.\n- To detect the pixels within the specified color range, the code applies a logical AND operator to create a binary mask of the pixels within the color range. - - The logical AND operator is applied to each color channel of the image separately using the \"\u0026\" operator, and then the results are combined using the \"\u0026\u0026\" operator.\n- Finally, the code displays the original image and the color detection result using the imshow() function and MATLAB's subplot() function.\n\n## Result \n\n\u003cimg width=\"407\" alt=\"Screenshot 2023-04-27 185229\" src=\"https://user-images.githubusercontent.com/68495520/234936118-52f9a4da-62eb-452f-b2c5-502fff4eb9e8.png\"\u003e\n\n## Contributing\nPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.\n\nPlease make sure to update tests as appropriate.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhinav2712%2Frash-detector","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhinav2712%2Frash-detector","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhinav2712%2Frash-detector/lists"}