j-manansala/image-warping j-manansala/image-warping

  • Stars
    star
    5
  • Rank 2,861,937 (Top 57 %)
  • Language
    Jupyter Notebook
  • Created almost 4 years ago
  • Updated almost 4 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
j-manansala/image-warping
github

j-manansala

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

In this notebook, we will learn how we can apply the homography matrix to adjust the camera perspective in images. We will show the potential and the limitations of the homography matrix in warping images.

More Repositories

1

image-differencing

In this notebook, we will learn how we can apply the image differencing to detect changes and movement in each frame of a video. We will also apply homography matrix and template matching to enhance our analysis of this problem further.
Jupyter Notebook
5
star
2

white-balancing

In this notebook, we will explore how the colors in the images can be corrected using white balancing techniques such as the white patch algorithm, gray world algorithm, and ground truth algorithm.
Jupyter Notebook
5
star
3

connected-components

In this notebook, we will explore how to automatically detect, label, and measure objects in images using connected components. This method improves on blob detection methods by grouping pixels based on their connectivity.
Jupyter Notebook
4
star
4

thresholding

In this notebook, we will explore how to conduct image segmentation using trial and error thresholding and Otsu’s method. We will also explore how the RGB and HSV color spaces can help pinpoint and segment objects in images.
Jupyter Notebook
4
star
5

object-detection

In this notebook, we will learn how we can find an object in an input image using template matching. We will also explore how the homography matrix can help address the template matching algorithm’s limitations by warping the image to achieve similar scales and orientations for the objects.
Jupyter Notebook
3
star
6

morphological

In this notebook, we will explore how to clean, prepare and enhance images using morphological operations. The operations like erosion, dilation, opening, closing, area_opening, and area_closing will be demonstrated.
Jupyter Notebook
2
star
7

histogram-manipulation

In this notebook, we will explore how the colors in the images can be corrected using histogram manipulation techniques. Various distribution functions will be implemented to see how they can affect the distribution of colors in the resulting image
Jupyter Notebook
2
star
8

blob-detection

In this notebook, we will explore how to automatically detect blobs in an image using the Laplacian of Gaussian (LoG), Difference of Gaussian (DoG), and Determinant of Hessian (DoH). This can be particularly useful when counting multiple repeating objects in an image.
Jupyter Notebook
2
star