- Average Filter (3x3, 5x5, 11x11, and 15x15). Analysis of using avg filter with different kernel sizes.
- Adding Salt and Pepper noise. Removing noise using median filter with different kernel sizes.
- Analysis of using Gaussian kernel with differnent kernel sizes for Blur effect.
- Generated a Gaussian and Laplacian pyramid.
- Performed Discrete Wavelet Transform using Haar classifier to remove High frequency component to smoothen the images.
- Performed Watermarking using DWT.
- Implemented Hough Tranform for circles from scratch.
- Camera Calibration using checkerboard.
- Implemented Harris Corner Detection from scratch.
- Image segmentation using K-Means clustering for:
- 3-D Color Space
- 5-D space, using extra two dimensions corresponding to x and y co-ordinate of pixel.
- Image segmentation using Mean-shift clustering.
- Face detection in an images using:-
- Skin color thresholding - Considered RGBA, HSV, YCrCb color space.
- Seeded Segmentation - Manually marking point in an image and recursively analyzing nearby points.
- Image Classification using Bag-of-Visual-Word with HOG and LBP features on CIFAR-10 Dataset.
- Image Classification: Extracted features from pretrained AlexNet model and classification using Random Forest Classifier.
- Convolutional Neural Network: Created our own architecture for CNN and performed 4 class classfication from CIFAR-10 Dataset.
- Image Identification and Matching: Matched using Brute-Force feature matching technique and plotted box for matched object in images.
- Panaroma Stiching: Stiched 3 Taj Mahal Images into 1.
- Computed Depth Map in given 2 images.