AI-supported image processing: Computer Vision

Computer vision (CV) is a branch of artificial intelligence and computer science that deals with the automatic processing and analysis of images and videos. The goal is to give AI models the ability to interpret and understand visual information similar to how the human eye does. AI-supported image processing enables companies to capture conditions and data in real time and use this data to optimize their processes. This data includes the current positions of load carriers (e.g., pallets), inventory levels, storage space fill levels, and the load status of trucks.

Computer vision for logistics

Computer vision enables the recognition and tracking of goods and the measurement of load carriers using cameras, right from goods receipt to pallet management and storage. Thanks to artificial intelligence, these systems gather increasingly accurate and informative data from digital images and videos, which companies can then use to make informed decisions. For this reason, computer vision is an extremely promising digitalization approach for the logistics industry, offering increased process transparency, optimized workflows, and thus savings in terms of effort. New methods from the fields of machine learning and AI can be used to automate a wide range of processes in distribution centers and warehouses.

Our services for computer vision

Based on many years of research in the field of computer vision, we support companies with the following areas of expertise:

Computer vision for companies: The ML Toolbox 

The importance of computer vision for logistics is reflected in research, as the topic was addressed in the large research project Silicon Economy. Here, researchers developed open source base components for AI algorithms. They then implemented two exemplary logistics use cases.

The basic components include the “ML Toolbox”, a software ecosystem that simplifies the use of various computer vision algorithms controlled by machine learning (ML). This is made possible by the provision of various services and the MLCVZoo software development kit. “MLCVZoo enables the integration of ML models from different frameworks via a uniform API, eliminating the need to integrate the frameworks individually for each new image processing project,” says Maximilian Otten, lead developer of the ML Toolbox. In addition, an intuitive AI-based do-it-yourself image processing service has been developed to facilitate the use of the ML Toolbox. “For our new Guided Training Service, companies do not need specialized IT expertise, just a basic understanding, so they can train an AI with just a few steps and minimal recruitment, depending on the complexity, in a matter of minutes,” explains Julian Hinxlage, who heads the “CV on Edge” project in which the service was developed. Overall, the ML Toolbox services cover the entire ML Ops pipeline for AI-supported image processing solutions.

Access the open source components of the ML Toolbox

At Fraunhofer IML, researchers are working not only on software but also on hardware for computer vision. They have developed a compact and inexpensive modular AI camera. Its key feature is the fact that the devices require no infrastructure other than Wi-Fi and electricity. The captured data remains largely on the camera, which also ensures the protection of personal data. The camera components are modular, commercially available parts. This allows the device to be customized to the individual use case.

Fraunhofer IML is leading the way for this innovative technology across numerous current use cases. The use of computer vision in logistics offers several advantages: