Homography Matrix

Have you ever wanted to know what would be the top view of a static image?

In image processing, we can perform the different transformations of images depending on our needs.

One of the sought after techniques are called Homography Matrix Transformation.

The homography technique is an image processing technique where we perform mapping of an image between two planar projections. It can simply be represented by a 3x3 Matrix.

You can perform different transformations using tomography such as perspective change, rotation, skew change, and the likes.

To better understand it, let us show some examples:

Let us…

Ready… Set.. Match!

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From our previous articles, we have discussed several image techniques that can be used to create different segmentation and conversion in the image.

This time, how about we talk about an image processing technique that can be used the same was object tracking.

Another useful processing technique as mentioned above is the so-called Template Matching.


Template matching refers to the image processing where we find similar templates in a source image by giving a base template to compared on.

The process of template matching is done by comparing each of the pixel values of the source image…

Using Image Processing Techniques to create a Machine Learning Dataset

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Image processing has been used in several applications, from computer vision to text detection, object detection, and many more.

One of its applications is that that you leverage your image processing techniques to create a sample dataset for your Machine Learning algorithm.

For this article, we will show how we can use simple image processing techniques as a pipeline for our machine learning models.

Suppose you have a random image, where there is an object that you want to predict, how can we extract necessary features and information that we…

RG Chromaticity

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In Part 1, we were able to discuss 3 Different Techniques(Thresholding, Otsu’s, and HSV Color Space) to segment different objects in an image.

This time, we will show a much more defined way of segmenting the objects using a much more complicated technique that is used for complicated images.

Let us say we have different kinds of unique colors in our image, how can we leverage an image processing technique to show the uniqueness of each pixel values?

The best way to do this is by using Chromaticity Segmentation.

In a sense, Chromaticity Segmentation looks at the combination of the…

Thresholding, Otsu’s and HSV Segmentation

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One of the most important contributions of image processing to data science is the ability to use the processing technique to create different segmentation over the image. By segmentation, we mean segmenting different objects from their background. Normally if we have a raw image, and we want to create a dataset of the objects in the image, we would want to first isolate these objects. But how can we do that?

We use different image segmentation techniques to isolate these distinct objects.

There are a lot of segmentation techniques that are frequently used but for part 1 of this article…

Finding the Connection!

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Image processing is primarily used to extract different features in an image. Since digital images contain different objects and information, it is evident that this kind of information is extracted from such images.

To do this, we can perform image processing techniques to single out and detect such features and objects. One of the most promising techniques is called Blob Detection.

A Blob, in a sense, is anything that is considered a large object or anything bright in a dark background, in images, we can generalize it as a group of pixel values that forms a somewhat colony or a…

Computer Vision, Programming

Morphing Time!

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One of the most essential image processing techniques out there is the so-called morphological operation.

As the name suggests, we use morphological operation in cleaning and correcting out the images. Normally, morphological operations are done after convolving an image to a specific kernel or spatial filter. Since the result of the spatial filtering is an image that shows different attenuated features, we would want them to be correct as a whole.

Sometimes, the resulting filtered image has broken lines or maybe joining other features that should be joined. This is where we use morphing. We again use a sort of…

Computer Vision, Programming

Giving Space...

One of the wonders of image processing is being able to see the pixel values of each image and perform different mathematical operations on it.

Since the image is already an array or a matrix, then we can already perform different operations like multiplying, adding, subtracting, and dividing.

One of the most used operation in image processing is convolution, which is primarily used for filtering the image.

The process usually stems from convolving an image array into a user-defined array or matrix.

This user-defined matrix are known as kernels and are usually have a different effect depending on the value…

Histogram Manipulation at its best!

Before we finish our discussion of image enhancements, it would be much perfect if we can discuss one of the widely used image enhancement technique which is Histogram Manipulation.

Normally an image can be seen either as super bright or super dark. A lot of image editing software can already do the adjustment of the exposure of the image itself, even before snapping that camera button, you can already use different filters to adjust the exposure of the camera shot/frame itself.

But what is the theory and mathematics behind it?

Histogram Manipulation

Histogram Manipulation is an image…

Part 2

For our Part 2 of Image enhancement, we would be dealing with one of the most important enhancement techniques, and that would the White Balancing Method.

White Balancing

White Balancing Method is an image processing technique where we correct the brightness and darkness of a specific image into different kinds of ground truth values that can be seen on the image itself.

They are various kind of technique on how to white balancing, some them are as follows:

  1. Ground Truth Method/White Patch Method
  2. Percentile Method
  3. Gray World Algorithm

Let us try to show each one of them!

For this article…

Ralph Caubalejo

Electrical Engineer/Data Scientist

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