ComputingComputer ScienceVision ScienceComputer VisionImage InterpretationMachine LearningEdge DetectionImage ClassificationObject DetectionObject RecognitionPattern RecognitionTexture AnalysisDistortionsGlass InspectionGlass Surface TextureMixture Of ClassifiersObjectsSurface InspectionTexture RecognitionVoting Classifiers
This paper addresses the problem of finding glass objects in images. Visual cues obtained by combining the systematic distortions in background texture occurring at the boundaries of transparent objects with the strong highlights typical of glass surfaces are used to train a hierarchy of classifiers, identify glass edges, and find consistent support regions for these edges. Qualitative and quantitative experiments involving a number of different classifiers and real images are presented.
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Contour and Texture Analysis for Image Segmentation
Jitendra Malik, Serge Belongie, Thomas Leung et al. · International Journal of Computer Vision · 2001 · 1.1K citations