Airplanes | Towards Data Science

So far, through image processing techniques, we have learned how to clean/preprocess irrelevant information, segment objects of interest, transform perspectives, and obtain essential features from our images. Just previously, we even applied machine learning in solving a classification problem. Does the realm of image processing end there? Negative! For this blog, we will tackle another important topic in the field — Template Matching.

Template Matching

Basically, template matching is the process of looking for the location of a template (aka reference) image from the source/input image. How is the algorithm implemented? Intuitively, it can be likened to how a convolution works since…

Leaves | 4k Wallpapers

Alas! The time has come!

The time has come for us to apply our image processing learnings to an actual machine learning problem. For this blog, let us solve a simple classification problem involving leaves. As a group assignment, our team were provided with a directory containing images of leaves coming from various plants. These images are presented as follows:

Homography Transform | OpevCV

So far what we have discussed is all about manipulating our images in such a way that we detect blobs, segment objects of interest, among others. How about manipulating these images in terms that we transform them from one form to another? Fret not, image processing got you covered! Welcome to a quick discussion on image transformation through the homography matrix.


Homography, also referred to as planar homography, is a transformation that is occurring between two planes. In other words, it is a mapping between two planar projections of an image. It is represented by a 3x3 transformation matrix in…

Image Segmentation | OpenCV

As exemplified in my previous article, we segmented the objects in an image using Color Image Segmentation through the HSV color scale. But that is not the only way we can segment our images. For this blog, we look at the image segmentation process under the lens of chromaticity segmentation.

Why should one prefer Chromaticity over RGB/HSV Segmentation?

  • We can get the ratios between RGB/HSV channels.
  • We can use target patches consisting of secondary colors and a mixture of other colors.

We formally define chromaticity segmentation as the process of extracting objects from images using the chromaticity space of the…

Segmented Tennis Ball | GitHub

Whenever we see images, it is composed of various elements and objects. In some circumstance, there might come a time that you would want to extract a certain object from the image. What would you do? Ah, I know. The first thing you will think of is to crop it, right? Well, that would somehow work. But there are irrelevant pixels that would be included, and I know for sure you do not want that. What if I tell you that we can obtain objects of interest using image processing techniques?

Welcome to Image segmentation using Python.

Image Segmentation

It is the…

Butterfly with detected blobs | EdLab

Images always tell story. Combining and complementing each individual component found in the image, a desired narrative can be drawn. And this is what people are after for — the big picture. However, what if you just wanted to examine each individual component independently on its own? Detaching it from the whole picture and creating a different story out if it. Fortunately, it is possible! Image components can be analyzed individually using blob detection techniques and the connected component algorithm.

Let us start with blob detection. Why is there a need for this?

Blob detection

It is among one of the final…

Morphological Operation applied to the Letter J | ResearchGate

Image processing is an interesting yet rigorous undertaking in the field of computing. What makes it more painstaking is the presence of nuances in the structure of these images undergoing analysis. Nuances may come in the form of noise, texture, and structure imbalance to mention a few. But do not fret image processing enthusiasts, for our researchers have found a way to account for these image imperfections and that is what we are going to talk about today — Morphological Operations.

Morphological Operations

Morphological image processing is an assembly of non-linear operations related to the morphology (shape) of features in an image…

Image obtained from Fotor

As the old adage says, an image can paint a thousand words. However, what if the story it conveys does not fit the narrative you wanted to see? You are certain that it should come from that image, but unfortunately it is just not vividly apparent. What if I tell you that it is possible to uncover the context you want to get out of an image and most probably get some additional insights along the way?

That is what we are going to talk about today — image enhancement!

Image enhancement is comprised of a set of techniques that…

Eye Digital Image | Wolfsdorf Rosenthal

As a recap to my previous article, images are more than just keepers of memoirs. It has been used in various applications out there, making significant impact in day-to-day processes in society. Now, we are going to look at images as numbers under the lens of matrices.

Wow! How can that be? Well, stick around and I am going to tell you the basic image processing techniques you should know as a starter.

But first, what is an Image?

Before digging deep into the technicalities, let us first dwell on the definition of the basic building block of image processing…

Old Vintage Box of Photos | Pikist

Memories are commemorated through the realms of the human mind. Our brains could only keep and process information so much that it tends to gradually forget fragments of these as time goes by. Fortunately, images were invented! Images keep us connected with our fond memories, through and through. But, enough of this sentimental babble. What point am I trying to get through?

While it is true that images are indeed keepers of history, is that their only purpose? Are they only good enough for photo albums that our parents would keep for personal consumption? Are they only fit for picture…

Matt Maulion

A kid who uses data to make a difference.

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