Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Контурный анализ× | Морфологические операции над изображениями× | |
|---|---|---|
| Область | Компьютерное зрение | Компьютерное зрение |
| Семейство | Machine learning | Machine learning |
| Год появления≠ | 1985 | 1982 |
| Автор метода≠ | Satoshi Suzuki and Keiichi Abe | Jean Serra |
| Тип≠ | Shape and contour analysis | Set theory and topological image processing |
| Основополагающий источник≠ | Suzuki, S., & Abe, K. (1985). Topological structural analysis of digitized binary images by border following. Computer Vision, Graphics, and Image Processing, 30(1), 32–46. DOI ↗ | Serra, J. (1982). Image Analysis and Mathematical Morphology. Academic Press. link ↗ |
| Другие названия | Edge-based contours, Boundary analysis | Mathematical morphology, Morphological filtering |
| Связанные | 5 | 5 |
| Сводка≠ | Contour analysis is the process of detecting and analyzing the boundaries of objects in images by identifying connected edges and extracting shape information. The Suzuki-Abe algorithm provides an efficient method for finding contours in binary images, enabling shape-based object classification and segmentation. | Morphological image processing, introduced by Jean Serra in 1982, is a technique based on set theory that reshapes and analyzes image regions using geometric structuring elements. Core operations include erosion and dilation, which can be combined into more complex operations like opening and closing, enabling noise removal, edge detection, and object analysis. |
| ScholarGateНабор данных ↗ |
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