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How to process image using machine learning

Image processing is the technical analysis of an image by using complex algorithms. In image processing, an image is an input, and useful information is the output. According to a report, the image processing industry will reach USD 38.9 billion by 2021.

Similarly, Artificial Intelligence industry is also witnessing considerable growth. According to Forbes, It is believed that AI and machine learning have the potential to create an additional $2.6T in value by 2020 in Marketing and Sales, and up to $2T in manufacturing and supply chain planning.

Previously image processing only involved analyzing the discrete objects in an image.  Making use of AI and machine learning can bring in a lot of changes in the image processing industry. Google Lens is one such application that makes use of deep machine learning and AI to process complex images.  Imagine you are walking around a Garden in some foreign country and you want to know the name of some flowers. Since you are in a foreign country, you can’t understand the language written on the information board. What would you do? No need to worry, Google Lens an app launched by Google, which uses Image processing techniques along with AI technologies and deep machine learning can come to your rescue again. Google Lens detects and understands what it detects to give actions based on that. The only thing you have to do is point your phone at a specific flower and then ask Google Assistant what is the object you’re pointing at.
AI has enabled in development of software that can recognize and describe the contents in an image. AI and machine learning can do real wonders in the field of image processing. Some of the changes that can be brought about in different industries are as follows:

Healthcare industry

Image analysis can be of great use in the healthcare industry. Computer vision software based on deep learning algorithms is already making things more comfortable in the healthcare industry. Such software is making automated analysis possible to deliver more accurate results at a fast rate. Most of the hospitals haven’t started using such technologies yet. When appropriately used, such technologies helps us to reduce dependency on manual analysis. From macroscopic to microscopic, including molecular imaging, can be made use of to achieve advanced and accurate diagnostic procedures. Image processing can play a crucial role in Tumor Diagnosis. Areas where machine learning and AI can be applied, are as follows:

  1. Medical X-ray: In most hospitals around the world, radiologists are made to study the X-ray to search for anomalies. By making use of automated image analysis with advanced deep learning algorithms, the burden on the radiologists can be reduced, and more accurate and faster results can be obtained. Such analysis can help radiologists in taking appropriate decisions. As a result, Radiologists need to focus only on those reports in which image analysis marks as important.
  2. Patients: Automated image analysis can be of great use to the patients. They no longer have to wait for days to know about their diagnosis results. The results they would be getting will be more accurate without any human errors.


Medical robots allow doctors to perform delicate diagnoses and surgeries by making use of extremely high-quality 3-D images that wouldn’t have been available otherwise. Even To know more about the benefits of image processing in the healthcare industry visit iflexion

Defense

Earlier it was challenging for the defense personnel to access some specific locations since they don’t know what lies ahead. The advancement of image processing has changed warfare completely. Remote-controlled drones can now be used to capture images of such locations and later analyzed using deep learning algorithms.
Surveillance cameras which gives an alert when a person is near the door can be even made to understand who that person is. Image processing can make it happen and will change the world completely. 

Automobile Industry

The Automobile industry has seen the maximum evolution in the past decade, but nothing can beat the innovation this industry is about to witness, which is- Self-Driving Cars. Self-driving cars are the future and are the greatest ever thing to happen in the industry. Self-driving cars do all the driving for us; in the meantime, we can do whatever we want. Imagine the world where would be reaching places without any traffic blocks and other difficulties. Doesn’t it look pretty impressive? Thanks to image processing and deep learning self-driving cars will help reduce the number of accidents also. Self-driving cars work based on Object detection. Object detection involves image classification and image localization. Image classification is identifying what the objects are in the image and image localization is about providing specific locations about this object. This is achieved by making use of AI and machine learning technologies.

To know more about self-driving cars and how they work visit: Towardsdatascience


Agriculture industry

Image processing, along with AI, can be a game-changer as far as the agricultural industry, is concerned. It can help improve the quality of the product. Image processing can be used to detect weeds. Weeds are foreign plants that grow in farms. These weeds compete with the crop for water and can affect the growth of crops.  Edge-based machine classifiers can help in identifying these weeds. Infrared image analysis helps in understanding and monitoring of irrigation techniques. Even the infrared image analysis can be used to predict the harvest time. Computer vision and image processing can also be used to grade fruits and food products based on color, size  and shape. Automated quality analysis of food products can help farmers save a lot.

Benefits of Image processing and how AI will change the world of image processing is not limited to the points mentioned above. We are still at the early stages of image processing, and we are yet to identify the maximum potential. Still, there exists confusion about whether the image processing has potential to that of human vision. There are also lots of issues associated with the storage of vast data that is captured by cameras all around the world. We are still conducting lots of research and analysis to explore more about the capabilities of image processing. We can hope that day is near where, technology will change the way we live.