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ブロブ検出×分水嶺セグメンテーション×
分野コンピュータビジョンコンピュータビジョン
系統Machine learningMachine learning
提唱年19981979
提唱者Tony LindebergSerge Beucher and Christian Lantuéjoul
種類Multi-scale feature detectionMorphological image segmentation
原典Lindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79–116. DOI ↗Meyer, F. (1994). Topographic distance and watershed lines. Signal Processing, 38(1), 113–125. DOI ↗
別名Connected component analysis, Region-based detectionWatershed transform, Water shedding segmentation
関連55
概要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.Watershed segmentation is a morphological image processing technique that automatically segments an image into distinct regions by treating image intensity as a topographic landscape where each object corresponds to a valley. Introduced by Beucher and Lantuéjoul in 1979 and refined by Meyer, the watershed algorithm is particularly effective for separating touching or overlapping objects.
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ScholarGate手法を比較: Blob Detection · Watershed Segmentation. 2026-06-17に以下より取得 https://scholargate.app/ja/compare