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Izjednačavanje histograma×Detekcija mrlja×
PodručjeRačunalni vidRačunalni vid
ObiteljMachine learningMachine learning
Godina nastanka1970s1998
TvoracSignal processing communityTony Lindeberg
VrstaContrast enhancement and preprocessingMulti-scale feature detection
Temeljni izvorGonzalez, 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 ↗
Drugi naziviHistogram stretching, Contrast enhancementConnected component analysis, Region-based detection
Srodne55
SažetakHistogram 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.
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ScholarGateUsporedite metode: Histogram Equalization · Blob Detection. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare