4 Industries That Benefit The Most From Image Segmentation

4 Industries That Benefit The Most From Image Segmentation .

One of the most powerful senses humans and animals have is the capacity to see things and process the images, pictures, and scenes they encounter. On any given day, the human eye captures and processes millions of images. However, very little has been done to understand the capacity of the human eye to recognize visual stimuli and for the brain, in turn, to process these images. Significant strides in this field were introduced when scientists and engineers developed image segmentation technology.

As explained by definitive guides like this, image segmentation has revolutionized a lot of the processes and tasks in numerous industries through its power of analysis, contrast, comparison, recognition, and detection. Coupled with artificial intelligence, machine learning, and neural networking, image segmentation is proving to be a highly promising technology that can vastly multiply human productivity. Here are some of the industries and sectors that are already reaping the benefits of image segmentation:

1. Healthcare Imaging

One of the first sectors to make use of the applications of image segmentation is the healthcare industry. The earliest uses of image segmentation have been in medical and diagnostic equipment and laboratory machines to capture, compare, and analyze images. Applications of image segmentation in medical imaging later evolved to include volume rendered images from computed tomography and magnetic resonance imaging (MRI).

For instance, image segmentation is one of the technologies used during the COVID-19 pandemic. Moreover, image segmentation is now being used to analyze sample tissues from patients to detect cancer and other pathologies. This technology has demonstrated wonders in locating tumors. It’s also very useful in measuring tissue volume. Further research and development of the practical applications of image segmentation are now extending to surgery planning, virtual surgery simulation, and intra-surgery navigation.

2. Security And Surveillance

Another sector that enjoyed the practical uses of image segmentation is the security and surveillance industry. Before the advent of image segmentation, police, law enforcement, and private investigators had to compare pictures manually through visual comparison for search and surveillance of faces and objects.

With the development of image segmentation, they can now feed images into computer systems and image comparison software. They’re now able to use the powerful processing capacity of image segmentation to come up with more nuanced and accurate analyses of pictures.

Aside from analyzing pictures, part of the work of security and surveillance professionals that’s been impacted by image segmentation is monitoring the flow of people in and around buildings, compounds, and complexes through closed-circuit television (CCTV) cameras. With image segmentation, camera manufacturers have developed CCTV cameras that can instantly recognize faces in a crowd and detect people under investigation or surveillance.

3. Gadgets And Smartphones Access

Another industry that has immensely benefited from the development of image segmentation is the electronics manufacturing industry. Before the development of image segmentation, smartphone and tablet users could only lock and secure their phones with alpha-numeric passcodes.

However, with image segmentation, smartphones and tablets can now be secured and locked using image detection security systems. Specifically, today’s technology enables you to limit access to your devices using facial recognition.

4. Self-Driving Vehicles

Self-driving vehicles have consistently been the subject of news in the past few years. Everyone’s amazed at how navigation system programmers and car manufacturers were able to make these machines drive smoothly in and around complex road systems under heavy traffic without any human driver. They’re able to stop at red lights, drive around rotundas, speed up in expressways, and crawl in bumper-to-bumper traffic all by themselves, and with very rare reports of accidents or collisions, if any at all.

Little do people know that the technology which serves as the foundation of self-driving autonomous cars is image segmentation. Vehicle navigation systems are programmed and developed by feeding hundreds of thousands of images to them. The self-driving car’s ‘brain’ is trained by making it ‘stare’ at images, pictures, and videos of streets, pedestrians, moving cars, parked cars, cars making turns, incoming traffic, animals crossing streets, and other objects that the vehicle can potentially meet on the streets.

Eye For Detail

One of the most powerful capabilities of image segmentation is its ability to appreciate images and simulate the human brain’s natural processes of object recognition, analysis, and comparison. Moreover, this technology can achieve these feats at a more detailed level, with greater capacity to detect nuances, and at a staggering depth and speed of analysis. Image segmentation will undoubtedly impact a lot more industries and benefit society in years to come.

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