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حوزهبینایی ماشینبینایی ماشینبینایی ماشین
خانوادهMachine learningMachine learningMachine learning
سال پیدایش199819851982
پدیدآورTony LindebergSatoshi Suzuki and Keiichi AbeJean Serra
نوعMulti-scale feature detectionShape and contour analysisSet theory and topological image processing
منبع بنیادینLindeberg, T. (1998). Feature detection with automatic scale selection. International Journal of Computer Vision, 30(2), 79–116. DOI ↗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 ↗Serra, J. (1982). Image Analysis and Mathematical Morphology. Academic Press. link ↗
نام‌های دیگرConnected component analysis, Region-based detectionEdge-based contours, Boundary analysisMathematical morphology, Morphological filtering
مرتبط555
خلاصهBlob 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.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.Morphological image processing, introduced by Jean Serra in 1982, is a technique based on set theory that reshapes and analyzes image regions using geometric structuring elements. Core operations include erosion and dilation, which can be combined into more complex operations like opening and closing, enabling noise removal, edge detection, and object analysis.
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ScholarGateمقایسهٔ روش‌ها: Blob Detection · Contour Analysis · Image Morphology Operations. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare