Image Segmentation using Graph Cut Simplified in Telugu💡 | Full Code Explanation(Easy Understanding)

In this video, I explained Graph Cut based Image Segmentation step by step in Telugu. This includes both theory + complete code walkthrough, so you can understand the concept clearly . 🔗 📄You can get Code & Report From here : https://github.com/Saichandana-123/Assignments-/blob/main/Computer%20Vision/Graph-cut%20segmentation/b23ee1077_computer_vision_assignment_2.py 💡 Topics covered: • What is Image Segmentation • Energy Function (Data Term + Smoothness Term) • GMM (Gaussian Mixture Model) explanation • Unary Costs (Why negative log likelihood?) • Graph Construction (Nodes, Edges, Source, Sink) • Min-Cut / Max-Flow algorithm • Pairwise smoothness (penalizing label differences) • Refinement (Morphological operations + Boundary smoothing) • Naive vs Graph Cut comparison 🎯 This video is useful for: • Computer Vision students • Lab assignments & projects • Viva preparation • Beginners who want clear intuition If you found this helpful, support the channel 🙌 Like 👍 | Share 🔁 | Subscribe 🔔 --- #GraphCut #ImageSegmentation #ComputerVision #Telugu #OpenCV #MachineLearning