What is “image analysis”? Easy-to-understand explanation of the mechanism and specific uses

• 1. What is image analysis?
• 2. Why image analysis is needed
• 3. How is image analysis performed?
• 4. When is image analysis used?
• 5. Benefits of introducing image analysis
• 6. Disadvantages of introducing image analysis
• 7. Who is good at developing image analysis systems and software?

What is image analysis?

Image analysis is a system in which a computer makes various decisions after an image is acquired using a sensor such as a camera. It also uses the recognition technology installed in the computer to understand the contents of the image, enabling information extraction and data conversion. The image is to recognize the characteristics of an object in image data such as photographs and videos, and to “mechanically determine what kind of object it is.”

For example, when a human sees an apple, he or she comprehensively looks at the shape, color, size, etc., and determines that this is an apple. The reason why we can make that distinction is that there are many judgment factors such as knowledge, perception, and memory that human beings have accumulated so far. Taking apples as an example, the following points will help you make a decision.

• “It has a shape close to a sphere”
• “The color is red or blue (green)”
• “It’s about the size of a baseball ball or a shot put the ball.”
• “There are dents at the top and bottom”
• “It has a calyx”

Image analysis performs this kind of information processing that humans naturally do on a computer. The computer that captured the image as data extracts the characteristics of the object and determines “what is reflected in the image?”. Technologies that are used in our daily lives include fingerprint recognition systems for smartphones and face recognition systems installed in digital cameras. Some digital cameras even have a smile detection function. With similar technology, “video analysis” that analyzes video is also advancing. Both refer to processing and analyzing images and videos with a computer to retrieve useful information.

Why image analysis is needed

There is a limit to the amount that can be visually diagnosed by the human eye, and it is impossible to analyze a large amount of image data instantly. On the other hand, continuing a lot of work is a specialty of computers. For image analysis, all you have to do is apply the captured image or video to the AI ​​analysis engine.

In the modern age of Rewa, where the promotion of telework and paperless operations is remarkable, there are increasing opportunities to handle images and videos in many businesses. Being able to perform a large amount of image analysis faster than humans and draw conclusions is a great business advantage. Below, we will introduce the image analysis mechanism in an easy-to-understand manner.

How is image analysis performed?

Image discrimination on a computer is a very sophisticated and complex process. This is because mathematical methods are required from object extraction to data arithmetic processing and final discrimination, without relying on the feeling of appearance and smell like human beings. In short,

• Extracting objects
• Arithmetic processing of extracted pixel data
• Discrimination based on calculation results

It is a mechanism that the image is analyzed through the procedure such as.

To explain these procedures in order, after acquiring the image data of the object, “image processing/extraction” is performed to make it easier to recognize mechanically. The procedure for image processing/extraction is as follows.

• Remove noise and distortion from the image
• Adjust brightness and color
• Emphasize the outline of the object
• Extract the area of ​​the object and distinguish it from the background
• Extract image data of an object in pixel units

Once you know what is in the image, the next step is to identify “what is the data of the extracted object”. This is the process of “judging an object from accumulated memories and experiences” when compared to humans. A computer is trained in advance with a large amount of “image data” and “labels (information about what the image data represents)”, and the object is identified from the information.

Nowadays, by combining it with AI technology (deep learning), it has become possible to discriminate images with higher accuracy. Technologies that combine image discrimination and deep learning include:

• Object recognition: Determines whether or not there is a specified object in space
• Face recognition: Identify an individual from the faces in the image
• Character recognition: Identifies characters are written on blog articles and YouTube thumbnails

With the development of AI, the accumulation and analysis of vast amounts of image data have progressed, and these are widely used not only at manufacturing sites but also in the fields of medicine and agriculture.

When is image analysis used?

From here, we will introduce examples of image analyses that are already active in various industries and businesses.

● “Inspection of products flowing on the production line” in the manufacturing industry

An image discrimination system can be used to label products flowing on conveyors. Labeling work performed manually has uneven accuracy and speed, and it tends to be difficult to allocate personnel according to the production volume. Therefore, by entrusting the process of checking the product with the robot and the image discrimination system and labeling the product in the correct position, it becomes easier to achieve quality averaging while greatly improving the work speed.

In addition, the beer bottles for recycling collected at the beer factory are checked by human eyes for cracks, and this visual system can also reduce labor costs. The use of image analysis is expanding in the manufacturing industry, such as the adoption of a system that automatically repels bottles in poor condition by photographing and analyzing beer bottles.

● “Pathological examination” to analyze X-rays and CT scans

At medical institutions and clinical laboratory centers, incorporating AI analysis into pathological diagnosis and examination will improve work efficiency and reduce the labor burden. The act of counting cells in a pathological test tends to be laborious. However, image analysis systems have evolved to complete within seconds. Complex analysis is possible, such as detecting objects that meet the conditions and not including unnecessary parts in the count results.

● “Detection of suspicious persons” at commercial facilities and event venues

Image analysis and video analysis systems are also expanding into the field of security. It is now possible to identify and track people in a space where many people gather.

For example, you can quickly narrow down similar people from camera images of a large number of people simply by specifying the characteristics (clothes, baggage) of the person to be monitored. Video analysis is better than human power to quickly check the accumulated camera images. In addition, you can track the behavior by identifying the position and time of the camera in which the target person was shown. Depending on the combination with an external system, it is possible to seamlessly receive and track alerts indicating that suspicious persons/objects have been detected.

The “face recognition system” that utilizes the human face itself is also being used more and more. Face authentication is one of biometric authentication and is a system that identifies and authenticates the person by extracting the face part from the image and collating it with the database. Faces are especially difficult to duplicate and forge, so they have come to be used in the field of security. The use of face recognition systems is expanding to various fields, from the use of smartphone apps to the security of financial systems and anti-terrorism measures.

The mechanism of the face recognition system and its advantages over conventional security will be explained in detail in the following articles.

■ Enhanced security with a face recognition system! Utilization of face path that spreads by improving accuracy

In addition to this, it can also be used for technical purposes such as extracting photos of our products from SNS posts and using them for marketing. If the analysis technology is further advanced, the range of applications is likely to expand, and image analysis is a field with future potential.

In addition, image analysis systems are increasingly being adopted from the perspective of crime prevention. A system is in operation that registers the data of a person with a criminal record in a computer in advance and constantly checks whether the person appears in the installed security camera. It is expected that this system will become more widespread to deter crime, such as strengthening anti-terrorism measures.

Benefits of introducing image analysis

There are two advantages to introducing image analysis.

● It leads to improvement of working environment

By combining image discrimination equipment with robots or systems, automation of the production process (FA) can be promoted. Speaking of inspection work, it is possible to inspect products without human hands by incorporating a program that removes or moves products using a robot arm in conjunction with an error in the image discrimination device. The system is free of fatigue, injury, and illness, so you can operate for long periods or work in dangerous locations without any problems. It will be easier for people to create a safe working environment, such as preventing long working hours and work-related accidents in dangerous areas.

● It will be easier to improve work efficiency and reduce labor costs.

Image analysis using a computer can detect small scratches and shape differences that are overlooked by the human eye. The information that can be processed by the human eye is limited, and there is a limit to preventing quality fluctuations due to individual skill differences and fatigue, but AI’s image analysis system can solve these problems. It is also possible to prevent oversights and false positives due to human error and to support high-speed lines, improving the accuracy of inspection work. The labor and personnel required for the work can be reduced, resulting in cost reduction.

Disadvantages of introducing image analysis

On the other hand, the introduction of image analysis also has its disadvantages.

● Costs will be incurred for the introduction of equipment such as cameras and monitors

With a high-performance image analysis system and high-resolution images, it is possible to find small things that cannot be found visually. However, it is costly to introduce such a high-precision system, so there is a disadvantage that it is not easy for companies with limited budgets.

● There are few image analysis apps and software that can be used for business.

When introducing an image analysis system in a company, choosing a system with the performance required for the business can balance the cost and the result. However, image analysis systems are not diverse, and it is difficult to find apps and software that fit your business and needs. There is a possibility that various systems will become widespread in the future, but image analysis is still a developing field.

Who is good at developing image analysis systems and software?

Image analysis has a high affinity with the field of artificial intelligence, and there are many cases where companies that specialize in AI development are involved in image analysis system development. How much effective data can be extracted from images is important for improving work efficiency, so if you request system development, choose a company that can effectively incorporate artificial intelligence. The following pages introduce recommended companies for system development using such artificial intelligence (AI). We have compiled the latest information on companies that specialize in image analysis systems and software development, so please check it out if you are in charge of introducing image