Image annotation services

High-quality data for Computer Vision applications

Image annotation for AI

Image annotation is the process of creating metadata in the form of labels for image data. This type of annotation is used to create datasets for computer vision models so they can identify images and extract the information needed to make accurate predictions.

Image annotation plays an important role in computer vision, the area of artificial intelligence that trains computers to interpret and understand the visual world. By using annotated or labeled images to train machine learning models, machines can accurately identify and classify objects and then respond to what they "see".

Computer vision applications include:

Autonomous vehicles that can track their surrounding objects with cameras and sensors, and react depending on what is happening in the environment.

Real-time inventory tracking and customer journey solutions for retail stores to optimize merchandise placement.

Manufacturing solutions for automated product assembly, defect detection, safety compliance and more.

LXT for image annotation

With LXT, you can quickly build a reliable data pipeline to power your computer vision solutions and focus your time on building the technologies of the future. The combination of our annotation platform, managed crowd, and quality methodologies deliver the high-quality data you need to build more accurate AI solutions and accelerate your time to market. Every client engagement is customized to fit the needs of your specific use case.

Our image annotation services include:

Bounding boxes

This is the most commonly used type of annotation for computer vision and involves using rectangular boxes to define target objects.

Image transcription

This task involves identifying and extracting text data from images to train computer vision solutions including Optical Character Recognition (OCR) systems.

Keypoint annotation

This type of annotation is used to label a single pixel in the image to indicate an object’s shape and to track variations in objects. It is often used for gesture and facial recognition.

Object detection

In this form of annotation, several objects are labeled in an image to make distinctions between different types of objects.

Image classification

With this image annotation method, the entire image is given a label so that a machine learning model can learn to recognize different characteristics of the same category of object.

Polygon annotation

This type of image annotation involves labeling images with irregular shapes and is the best way to ensure pixel-level precision.

Image captioning

Assigning a natural language description to images allows insights to be extracted that can help improve a variety of applications, from search results to captioning tools for video, and more.

Semantic segmentation

This image annotation method involves outlining the boundaries between similar objects. It is used for autonomous vehicles, medical image diagnostics, and more.

Image evaluation

Review and evaluate image quality for continuous improvement.

Secure services

With the accelerating volumes of data created daily and the number of potential threats on the rise, security is an increasing area of concern for organizations across all industries. Our platform and processes are designed to ensure the security of your data.

To meet the most stringent security requirements, our facilities are ISO 27001 certified and PCI DSS compliant. We also offer supervised transcription within a secure facility to safeguard your data. We will work closely with you to design a secure solution that meets your needs.