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| Uśrednianie histogramu× | Dopasowywanie wzorca× | |
|---|---|---|
| Dziedzina | Widzenie komputerowe | Widzenie komputerowe |
| Rodzina | Machine learning | Machine learning |
| Rok powstania≠ | 1970s | 1980s |
| Twórca≠ | Signal processing community | Computer vision community |
| Typ≠ | Contrast enhancement and preprocessing | Pattern matching and detection |
| Źródło pierwotne≠ | Gonzalez, R. C., & Woods, R. E. (1992). Digital Image Processing. Addison-Wesley, 2nd edition, Chapter 3. link ↗ | Lewis, J. P. (2004). Fast normalized cross-correlation. Vision Interface, 120–123. link ↗ |
| Inne nazwy | Histogram stretching, Contrast enhancement | Correlation-based matching, Similarity matching |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | Histogram equalization is an image preprocessing technique that redistributes pixel intensities to improve contrast and visibility of details. By spreading the histogram of pixel values evenly across the available range, histogram equalization enhances images with poor contrast, making features more visually distinct and easier to process algorithmically. | Template matching is a straightforward technique for locating a known pattern (template) within a larger image. By sliding a template image across the target image and computing a similarity measure at each position, template matching identifies locations where the template appears. It is effective for simple object detection when templates are well-defined and appearance variation is limited. |
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