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| Analiza konturu× | Detekcja obszarów (blob detection)× | |
|---|---|---|
| Dziedzina | Widzenie komputerowe | Widzenie komputerowe |
| Rodzina | Machine learning | Machine learning |
| Rok powstania≠ | 1985 | 1998 |
| Twórca≠ | Satoshi Suzuki and Keiichi Abe | Tony Lindeberg |
| Typ≠ | Shape and contour analysis | Multi-scale feature detection |
| Źródło pierwotne≠ | 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 ↗ | Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79–116. DOI ↗ |
| Inne nazwy | Edge-based contours, Boundary analysis | Connected component analysis, Region-based detection |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | 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. | Blob detection is a technique for identifying regions of interest (blobs)—connected, homogeneous areas that differ from their surroundings—at multiple scales. Introduced by Lindeberg in the context of scale-space theory, blob detection automatically finds and characterizes circular or elliptical objects without requiring a priori knowledge of their size. |
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