Discover j-manansala/blob-detection Open Source project

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Jupyter Notebook
Created almost 4 years ago
Updated almost 4 years ago

j-manansala

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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.

image-warping

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.

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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.

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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.

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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