The assignments for the class Introduction to Computer Vision, Spring 2020
Basic image analysis operations:
- Generating an histogram for an image
- Implementing and applying Otsu's thresholding method
- Implementing and applying Dilation and erosion operations to an image
- Implemented in MATLAB, Assignment grade: 90
Assignment based on basic level deep learning knowledge
- Implementing Logistic Regression classification algorithm both with iterative (for loop based) and matrix based approach
- Parameter fine-tuning with Logistic Regresion classifier
- Modification of the CNN model provided in https://github.com/keras-team/keras/blob/master/examples/mnist_cnn.py
- Testing and fine-tuning the model with AdaDelta and SGD optimizers
- Implemented in Python (in a form of a notebook file), Assignment grade: 96
Assignment for testing Edge Detection and Edge Linking techniques
- Applying Sobel and Prewitt operators to perform basic leel edge detection
- Applying Canny Edge Detection and performing parameter optimization for this technique of edge detection
- Implementing Hough Transform algorithm from scratch
- Analysis for all pf the methods mentioned
- Implemented in Python (in a form of a notebook file), Assignment grade: 95