Introduction to Image Processing: Image Formation on Camera, Camera Mechanism, Perspective Transformation, Image Transformations, Concept of convolution, Concept of Masks, Fourier series and Transform. Features and filters: low-level vision, Linear filters, Edges and contours, Binary image analysis, Background subtraction, Texture Motion and optical flow. Grouping and fitting: mid-level vision: Segmentation and clustering algorithms, Hough transform, Fitting lines and curves, Robust fitting, RANSAC, Deformable contours, Interactive segmentation. Multiple views: Local invariant feature detection and description, Image transformations and alignment, Planar homography, Epipolar geometry and stereo, Object instance recognition, Image warphing, Image stitching, Harris corner detection-interest point detection ,SIFT descriptor, Viola Jones Face detector, Cascading Classifiers for detection. Recognition: high-level vision: Basics of Object detection and recognition, Supervised classification algorithms, Deep learning, Convolutional neural networks.