10 types of image annotation and its use cases
Image Annotation can be defined as a process of manually defining areas in an image and creating descriptions of those areas. Image annotation is used to train machine learning and has over the time been used in the field of agriculture, medicine, advertising, and retail shops. There are several types of image annotation and their use cases. Below are ten of types and its use cases.
Image Annotation can be defined as a process of manually defining areas in an image and creating descriptions of those areas.
Image Annotation can also be seen as a process of labeling an image to show its data features and what you want your model to recognize.
Image Annotation is used to train machine learning Algorithms for computer or machine vision appliances.
Examples of industries that use these services are the health sectors, Automotive companies, Agriculture, Retail, Advertising and Clothing companies.
Image Classification is a form of Image annotation that seeks to identify similar objects depicted in images across a data set.
Use case: Industries well noted for using this type of image annotation are the health or medicine sector for medical imaging.Image classification is also useful for object identification in satellite image or Machine vision.
Other sectors who employ the use of Image annotation are the retail, Agriculture and advertising companies
Object detection is a form of annotation that involves identifying the presence, position and number of one or more objects in an image and annotating them as accurately as possible.
Use case: Companies who use this service or method are security companies, Agriculture sector for Animal detection and people detection.
The health or medicine sector for featured detection in healthcare also uses this type of Image annotation. The retail sector also uses Object recognition for object detection and lastly, the transportation sector for vehicle detection with Artificial Intelligence.
This is a type of image annotation which helps us differentiate objects in a given image. It enables corporate entities to organize data within images into categories.
Use case: Automotive companies use this type for the manufacturing of self-driving cars. Clothing companies also use this type for their virtual fitting rooms. Another sector which uses this type is the healthcare/medicine for medical imaging, diagnoses and scans such as the MRI scans.
This is a type of Image Annotation which refers to the borders that enclose an image. It is used to serve as a reference point for object detections.
Use case: Automotive companies use this type for Vehicle damage detection. Insurance companies also use this type to enable them to pay claims from customers with accidented cars.
Companies who manufacture Drones and Robotic imagery also use this type of image annotation. Lastly, online retail shops also use this type in their line of business
The 3D cuboids type of Image annotation is similar to the bounding boxes but this type has a task of labeling objects in 2D images with cuboids.
Use case: This type is used for the training of Robots, Automotive companies for self-driving cars and also to identify the depth of objects such as buildings by construction, Engineering or Architecture firms
Landmark Annotation is a type of image annotation used to label key points at specific locations.
Use case: Companies who use this type of image annotation are those who develop counting applications, Images for maps, unlocking cell phones and identifying people on social media applications.
This is a type of image annotation that is used to train warehouse robots to be able to place boxes or items accurately in a row.
Use case: This type is used by companies who manufacture autonomous vehicles or self-driving vehicles
This is a type of image annotation that is used for object detection. It enables a computer vision device to search and locate an object.
Use case: This type is used by the medical field for CT scans, the automotive companies for the detection of damages in cars.
It is useful in the Agricultural sector to monitor growth of plants and also by the retail shops for detecting of products in a shopper’s basket
Instance Segmentation is a type of image annotation which is similar to semantic segmentation. This method identifies each time an object occurs. It is a computer task that is used for detecting and localizing an object.
Use case: Automotive companies use this type of image annotation for self-driving cars.
This type of annotation is used to draw circles on a chart to annotate different areas of a data on a chart.
Use case: Companies that use this type in their businesses are the manufacturing, automotive, retail shop, agriculture and the medical sector.
A complete state of the art where we review how computer vision works, the different techniques used, the main multi-sector use cases and the challenges ahead.
In order to please customers and increase profits, post and parcel businesses were already looking towards more efficient and affordable delivery systems before COVID-19. Find out in this article How Computer Vision recognizes objects for safer package deliveries
The itobos project will enable physicians to diagnose skin diseases earlier and with greater accuracy, increasing the effectiveness and efficiency of personalized clinical decisions. Discover the projet and the role of isahit in it.
We have a wide range of solutions and tools that will help you train your algorithms. Click below to learn more!