The objective of this task is to implement a basic edge detection algorithm using convolutions and kernels.
- Convolutional operations with predefined kernels are widely used for tasks like edge detection. In this task, you will explore the concept of convolutions and kernels to implement an edge detection algorithm.
- Your task is to implement an edge detection algorithm. You may use predefined kernels like the sobel/scharr/feldman or any other operators of your choice. You will apply convolutions with predefined kernels to detect horizontal and vertical edges in a given image.
- The results should be something like the following:
- DEADLINE - 19/12/2024 EOD
- A colab folder with both your python script and report
- A Python script or Jupyter Notebook containing your implemented algorithm along with comments and explanations for each step.
- A markdown file or a latex pdf, documenting all the experimentation you did, explaining various results, comparing different methods etc.
- This is a graded assignment and will be judged on the results. (Brownie points for good coding practices)
- Directly importing an edge detector from a library is not allowed.
- Define the operators/filters/kernels you're using yourself don't use any library to import them.
- Directly copy pasting from the internet(without knowing/learning each and every line) or simple copy pasting from your peers would lead to deratification.