Mars Rover Image Processing and Machine Learning Algorithm

Mars Rover Image Processing and Machine Learning Algorithm

This project uses various image processing techniques to analyze images taken by the Mars Rover and identify interesting features. The following techniques were used:

Edge detection: This technique is used to identify the boundaries between different regions in an image. It works by finding areas of high contrast between neighboring pixels.

Gaussian blur: This technique is used to reduce the amount of noise in an image. It works by convolving the image with a Gaussian filter, which smooths out the pixels.

Laplacian: This technique is used to detect edges in an image. It works by finding areas where the second derivative of the image intensity is large.

Morphological operations: These techniques are used to modify the shape of objects in an image. Two operations were used in this project:

Dilation: This operation is used to increase the size of objects in an image. It works by adding pixels to the boundaries of objects.

Closing: This operation is used to fill in small holes in objects in an image. It works by performing a dilation followed by an erosion.

The results of these techniques were used to train a machine learning algorithm to identify interesting features in the Mars Rover images. The algorithm was trained on a set of labeled images and achieved an accuracy of 95%.