képfelismerés

Képfelismerés, often translated as image recognition or computer vision, is a field of artificial intelligence that enables computers to interpret and understand visual information from images or videos. It involves a range of techniques and algorithms designed to identify objects, patterns, scenes, and activities within digital visual data. The goal is to enable machines to "see" and "understand" the world in a manner similar to human vision, though through computational processes.

The process of képfelismerés typically begins with image acquisition, where an image or video is captured by a sensor like a camera. This raw data is then preprocessed to enhance its quality and reduce noise. Feature extraction is a crucial step, where algorithms identify distinctive characteristics or patterns within the image, such as edges, corners, textures, or colors. These extracted features are then fed into a classification or recognition model, which has been trained on a large dataset of labeled images. The model compares the features of the new image against its learned patterns to identify and classify objects or scenes.

Képfelismerés has numerous applications across various industries. In healthcare, it assists in diagnosing diseases by analyzing medical scans. In the automotive sector, it powers autonomous driving systems by detecting pedestrians, vehicles, and traffic signs. It is also used in security for surveillance and facial recognition, in retail for inventory management and customer analytics, and in entertainment for image and video search. The field continues to evolve rapidly, with ongoing research focused on improving accuracy, efficiency, and the ability to handle complex and varied visual scenarios.