K-means clustering solution to the NP-hard image segmentation "paint by number" technique, where input image's color dimensionality is smoothened, boiling down source coloration clusters most similar to user-selected color regions.
git clone https://github.com/chasem51/color42wo.git
cd color4wo
firebase login
firebase serve && firebase deploy
- Angular
- jQuery
- bootstrap
- Image credits: Chase Maivald
- References
- 1: Automated Brain Tumor Detection & Segmentation from MRI Shelke, Sanjay M., and Sharad W. Mohod. “Automated Segmentation and Detection of Brain Tumor from MRI.” 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018. https://doi.org/10.1109/icacci.2018.8554807.
- 2: Comparitive Study of Data Clustering Techniques Khaled Hammouda, A Comparative study of Data Clustering technique. Department of System Design Engineering, University of Waterloo, Canada.
- 3: Image Segmentation using K-means Clustering Algorithm and Subtractive Clustering Algorithm Aimi Salihai Abdul, Mohd Yusuff Masor and Zeehaida Mohamed , Colour Image Segmentation Approach for Detection of Malaria Parasiter using Various Colour Models and k-Means Clustering, In WSEAS Transaction on Biology and Biomedecine., vol. 10, January (2013).