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Histogramegalisatie×Contouranalyse×
VakgebiedComputer visionComputer vision
FamilieMachine learningMachine learning
Jaar van ontstaan1970s1985
GrondleggerSignal processing communitySatoshi Suzuki and Keiichi Abe
TypeContrast enhancement and preprocessingShape and contour analysis
Oorspronkelijke bronGonzalez, R. C., & Woods, R. E. (1992). Digital Image Processing. Addison-Wesley, 2nd edition, Chapter 3. link ↗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 ↗
AliassenHistogram stretching, Contrast enhancementEdge-based contours, Boundary analysis
Verwant55
SamenvattingHistogram 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.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.
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  2. 2 Bronnen
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  1. v1
  2. 2 Bronnen
  3. PUBLISHED

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ScholarGateMethoden vergelijken: Histogram Equalization · Contour Analysis. Geraadpleegd op 2026-06-15 via https://scholargate.app/nl/compare