Why Image Annotation is Essential for Your Business

You must have seen one of those movies where a drone or a camera is used to identify a target by the cops or the investigative agencies. These thriller and action sequences often use technology that helps them identify the culprit and complete the mission. A more common example that you may find closer to you almost daily is using security cameras to check cars that are speeding above the permissible limit. The systems are so mature these days that it is impossible to fool a security camera anymore. The technology behind both these examples is known as computer vision.

Image annotation helps the computer understand the visuals by labeling with text, annotation tools, or both. The activity of image annotation is part of the machine learning process that helps create a set of a database with which you expect the computer to continue recognizing visuals on its own. It is helpful in various industries like e-commerce, logistics, agriculture, healthcare, security, surveillance, etc.

We are going to understand why image annotation is essential for your business.

What is image annotation?

Image annotation is a process of labeling images as part of the machine learning model. It helps the computer understand the visuals on its own after the dataset is completed.

The process of image annotation is usually done in a computer-assisted model. The engineer is expected to define the labels – also known as classes – and provide image-specific information to the computer.

After the engineer has labeled all the images in a dataset, the computer will continue to recognize the predetermined features in the new images that the engineer has not labeled.

Importance of image annotation

Image annotation typically involves a lot of manual work to make the computer understand the various objects in an image by labeling. It is an important exercise to annotate photos with labels to empower computer vision abilities. Here is why image annotation is essential for businesses today:

Object detection

Image annotation allows the computer to detect the various objects in a machine learning process. Whether your system is powered by artificial intelligence or machine learning, you need to train the system via image annotation to understand the various objects. The engineering or team of engineers would help the computer vision understand the various elements seen in the visuals.

Object classification

Image annotation does not limit itself to object detection. You can also classify the various objects in various categories as part of this exercise. For instance, there could be a car, a man, and a cat in the same image. You can classify them into three different categories to help the computer understand more about the objects in the image. This helps in getting more accurate information as per the project’s requirements.

Validation data

Image annotation is essential for a business because it can create model validation training data that helps computer vision to understand the next set of images on its own. It is a critical feature to enable the computer to use artificial intelligence.

Accuracy

Image annotation increases the level of accuracy of the computer vision in the project. If you are solely dependent on the data from other projects to help the computer vision understand the objects, you may have limited success. It is better to do image annotation in a real-world scenario in the project and use that as a foundation for the project.

Image annotation is an integral part of any business process that aims to use machine learning to empower the computer to understand the visuals on its own.

How to do image annotation?

There are various ways by which you can do image annotation. It is a mix of processes, software, and people. You can choose any of the following options to annotate images:

Internal team

You can set up an internal team for image annotation or data annotation. You can use your existing resources or hire additional staff to annotate photos using an image labeling tool. However, it has been seen that setting up an internal team is expensive and tough to scale.

Freelancers

You can also hire freelancers to provide image annotation services. You will have to train these freelancers to understand your business requirements. Compared to the other options, hiring freelancers is cost-effective but not a reliable method. As the data annotation being done as part of this exercise is very important for the organization, you should have complete trust in the freelancers you hire for your requirement.

Crowdsourcing

Third-party platforms can be used to hire freelancers to provide annotation services. In this case, you are using the platform and are unsure who is working on your project individually. The quality of the work provided under the crowdsourcing model is often not at par with the other models, like in-house teams or outsourcing.

Outsourcing

You can always hire a specialist firm for image annotation The outsourcing company is expected to provide data labeling services per your requirements. It is cost-effective to do image annotation, as you can easily scale your activities according to project requirements.

If you are looking for a cost-effective and easy-to-scale method, you should go for outsourcing. This way, you will get the image annotation services of an expert team. You can also expect more agility in the processes, a better communication loop, and better quality and expertise.

It would help to consider factors like expertise, quality, agility, and contract terms for finalizing a data labeling partner for image annotation. These are some factors that you can consider for selecting the right image annotation service provider.

As image annotation sets the foundation for your project, it is critical to have the right partner by your side. Always run a thorough check on the past projects delivered by the company before selecting a partner for your project.