Applied KMeans++ algorithm to achieve the goal of image segmentation.
Image Segmentation is the process by which a digital image is partitioned into various subgroups (of pixels) called Image Objects, which can reduce the complexity of the image, and thus analysing the image becomes simpler.
We use various image segmentation algorithms to split and group a certain set of pixels together from the image. By doing so, we are actually assigning labels to pixels and the pixels with the same label fall under a category where they have some or the other thing common in them.
Using these labels, we can specify boundaries, draw lines, and separate the most required objects in an image from the rest of the not-so-important ones.
For more knowledge on Image Segmentation and its techniques follow: Image Segmentation
The clustering based techniques segment the image into clusters or disjoint groups of pixels with similar characteristics. By the virtue of basic Data Clustering properties, the data elements get split into clusters such that elements in same cluster are more similar to each other as compared to other clusters.
Original image before segmentation:
After performing Image Segmentation using KMeans++ algorithm the output obtained is:
