In this post, we will look at an overview of the 3 topics. A Homography Matrix is defined as the mapping between two planar projections of an image. It is represented by a 3x3 transformation matrix in a homogenous coordinates space. …

Image segmentation using the different types of channels and thresholds may not work in cases where the wanted colors are not obvious. Instead, we look at the RG Chromaticity space to mask our image. Chromaticity Segmentation relies on the RG Chromaticity space, a two-dimensional representation of color that removes information…

From the original image of an orange bean bag on white tiles, the various representations can be seen. The gray scaled image with a threshold set to make it binary, the green channel, the saturation channel, and finally the masked and segmented image of only the bean bag. …

Blob Detection, as the name suggests, allows us to detect objects of interests (blobs) in our image. Blobs are defined as bright objects in a dark background or vice versa. We will be using three methods to automatically detect our blobs: Laplacian of Gaussian (LoG) — takes the laplacian of…

Similar to Spatial filters, Morphological operations use neighboring pixels to transform pixel intensities that reduce/increase the size of the focus in a “filter” or structuring element. These operations are useful for cleaning images. …

Spatial filters assign the value of a pixel based on their neighbors. Filters are defined as matrices, known as kernels, and are applied to an image through an operation known as a convolution. The image being used for this post is a rgb2gray converted lena image. Each kernel is a 3x3 pixel image with numbers that determines how the image will be affected. In the example of horizontal and vertical sobel filters, the horizontal and vertical points are being focused on. In the example of the Gaussian blur, pixels in the center are focused on and corner pixels are blurred. This creates a bokeh effect.

To start off my blog posts, we will quickly look at digital images with a different perspective for image processing using Python. At the surface, images come in different filetypes such as png, jpeg, jpg, bitmap, etc. However, like all things digital or computer related, they need to have a…

The previous post introduced the distribution plots of the channel values. Let us consider this dark image. The histogram of the channel values shows that most pixels have low intensity values. We want to make this distribution uniform, which is equivalent to making the CDF (blue) linear (red).

White Balancing is a method to color correct images with an overlaying tint, by making known white areas in the image appear white. There are 3 methods to achieve this: We will study this snowy mountains picture. A blue tint is common on images with snow. This is usually because…