Computer vision and machine learning methods for digital restoration
Abstract
This article examines the primary computer vision methods of the OpenCV library designed for automated object detection, recognition, and classification in digital images, aimed at providing information for decision-making and subsequent processing. Based on the analysis of image segmentation methods and algorithms, feature extraction, object detection and recognition, as well as clustering, the authors propose solutions to optimize their performance and adapt them to the applied task of digital restoration of objects of historical and cultural heritage.
Fields of Study & Subjects
Image Processing and 3D Reconstruction
Advanced Neural Network Applications
Computer Science and Engineering
Publication details
- Journal / source
- AIP conference proceedings
- Volume
- 3390
- Pages
- 060013–060013
- Publication date
- 1 January 2026
- Language
- EN