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Histogramutjevning×Konturanalyse×
FagfeltDatasynDatasyn
FamilieMachine learningMachine learning
Opprinnelsesår1970s1985
OpphavspersonSignal processing communitySatoshi Suzuki and Keiichi Abe
TypeContrast enhancement and preprocessingShape and contour analysis
Opprinnelig kildeGonzalez, 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 ↗
AliasHistogram stretching, Contrast enhancementEdge-based contours, Boundary analysis
Relaterte55
SammendragHistogram 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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ScholarGateSammenlign metoder: Histogram Equalization · Contour Analysis. Hentet 2026-06-15 fra https://scholargate.app/no/compare