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Uśrednianie histogramu×Detekcja obszarów (blob detection)×
DziedzinaWidzenie komputeroweWidzenie komputerowe
RodzinaMachine learningMachine learning
Rok powstania1970s1998
TwórcaSignal processing communityTony Lindeberg
TypContrast enhancement and preprocessingMulti-scale feature detection
Źródło pierwotneGonzalez, R. C., & Woods, R. E. (1992). Digital Image Processing. Addison-Wesley, 2nd edition, Chapter 3. link ↗Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79–116. DOI ↗
Inne nazwyHistogram stretching, Contrast enhancementConnected component analysis, Region-based detection
Pokrewne55
PodsumowanieHistogram 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.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.
ScholarGateZbiór danych
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  1. v1
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  3. PUBLISHED

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ScholarGatePorównaj metody: Histogram Equalization · Blob Detection. Pobrano 2026-06-15 z https://scholargate.app/pl/compare