When people are asked about semantic segmentation, the common answer is a blank stare that expresses a lack of understanding of the subject matter. It’s fairly new, and it requires an expert to explain it clearly and concisely. 

However, if you’re hungry for information and want to constantly learn and evolve with the environment, this article is going to try to explain what semantic segmentation is about. 

What Is Semantic Segmentation?

Here’s the million-dollar question: what is semantic segmentation? The most straightforward explanation is that semantic segmentation involves classifying each pixel in an image and labelling it accordingly. 

In short, every pixel in an image needs to be paired with proper classification. For example, the image is of five people in a room. Each person is given a single label of person, and the pixels making up the image of each person is further classified and labelled again as person.

Confused? Let’s take a deeper dive.

There are two main tasks in semantic segmentation. These tasks are classification and detection. When you classify, you group an image in an identical category. Meanwhile, detection refers to identifying an object and localizing it.

Semantic segmentation has been used in many fields and industries. This includes the medical field, automotive industry. It has even been used for maps, lands, and road signs. The classification process makes it easier to detect environmental changes that can aid in the improvement of one’s daily life.

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History Of Semantic Segmentation

Semantic segmentation has already been around before 2000 when it was still called digital image processing. Segmentation and clustering have already been applied, and tech experts continued pushing through to make breakthroughs. 

The next decade, four methods came to light, and these were known as clustering segmentation, classification, graph theory, and a combination of clustering and classification. Ever since, many other models popped into view. A few years later, by the end of 2017, hundreds of models have been released and ready to be used by the public.

Advantages Of Semantic Segmentation

While there is confusion about semantic segmentation, it’s actually quite useful. Many people enjoy the benefits of semantic segmentation without realizing it. To make it clearer, here are a few advantages of the process.

1. Identify medical images

Aside from the doctors’ expertise, you can’t deny that in the medical field, everyone relies so much on technology. Every year, there’s a new advancement introduced to better study the health situation of individuals. Technological advancements provide more accurate results which help doctors and medical professionals pinpoint what diseases or illnesses their patients are suffering from.

Examples of semantic segmentation in the medical field include the ability to identify medical images—x-rays, CT scans, MRI scans, you name it. Likewise, the ability to identify what bacteria are present in smears is also brought by semantic segmentation. Diagnostic tests have upgraded and have become better now with developments in the field of semantic segmentation.

2. Autonomous systems

Autonomous systems involve self-driving cars and drones that make use of semantic segmentation. The system has been helpful in these situations because semantic segmentation can identify road signs and label them to help self-driving cars properly navigate the road. Likewise, self-driving cars can detect if the region is drivable or not.

Because of semantic segmentation, the chances of accidents are significantly reduced and more people will feel safe on the road. 

3. Analysis of geographical images

There are still many parts of the world that are undiscovered, but thanks to semantic segmentation, the blockage can now be removed. Semantic segmentation allows for the identification and segmentation of different types of land. Thus, it’s easier to map out areas in regions that need to be developed. 

Conclusion

Semantic segmentation has been really helpful in facilitating developments in the world everyone lives in. There are many new possibilities with semantic segmentation being closely monitored by developers. Doors have been opened and people have been benefitting from the latest developments. 

Now, people enjoy the best healthcare offerings because more accurate results are coming out from tests. Likewise, people feel safe when they drive and walk because car systems can now identify road signs and even navigate complicated processes involved in going from one place to another.