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Glossary

Image recognition

What is Image recognition?

Image recognition is a field of computer vision in which software identifies what an image shows – objects, people, text, logos or scenes. It is usually based on neural networks trained on large numbers of labelled images. Applications range from quality control in manufacturing and sorting product photos to supporting medical imaging. With images of people, data protection and potential bias require particular attention.

How KI.ordo helps

KI.ordo does not offer image analysis; agents and flows process text only.

Topics

  • Computer vision
  • Image analysis
  • Deep learning

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Related terms

Computer vision

Computer vision is a field of AI in which computers interpret images and video. Typical tasks include detecting and locating objects, reading text in images and measuring components. The technology is used, for example, in quality control in manufacturing, in driver assistance systems, in logistics and in medical imaging.

  • image analysis
  • deep learning
  • +1

Convolutional neural network (CNN)

A convolutional neural network (CNN) is a neural network architecture particularly suited to image data. It scans the input with small filters, detecting simple features such as edges in the first layers and more complex shapes in deeper ones. CNNs shaped image recognition for many years and are used, for example, to spot defects in product photos or in medical image analysis.

  • neural network
  • image recognition
  • +1

Instance Segmentation

Instance segmentation is a computer vision technique that detects every individual object in an image and outlines it pixel by pixel. Unlike semantic segmentation, it also distinguishes between objects of the same class: three people receive three separate masks rather than one shared area. It is used, for example, in quality inspection, medical imaging, robotics or counting products on a shelf.

  • Computer vision
  • Image analysis
  • +1

Optical character recognition (OCR)

Optical character recognition (OCR) converts text contained in images, such as scans, photos or faxes, into machine-readable text. Only then can documents be searched, copied or processed automatically. Modern OCR uses neural networks and can also recognise tables, layouts and, in some cases, handwriting. Typical uses include invoice processing, archive digitisation and reading forms; quality depends heavily on image quality.

  • documents
  • text recognition
  • +1