Paper
31 May 1996 Gray-scale morphology for small object detection
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Abstract
In this paper, we present morphological processing using median operation for small object detection. First, we perform median morphological operation on the gray-scale image with structuring element A and make all scene regions of size equal to the central A's area or larger brighter (for bright objects) or darker (for dark objects) and other regions approximate invariably. Second, we perform median morphological operation on the gray-scale image with larger structuring element B and make all scene regions of size equal to the central B's area or smaller darker (for bright objects) or brighter (for dark objects) and other regions approximate invariably. Third, we calculate the absolute difference of above two outputs. All object regions between the smallest and largest will be enhanced and all background regions will be weakened. Then a simple threshold can extract all objects with some smaller background regions. Finally, those smaller background regions whose areas are smaller than structuring element A can be eliminated by region labeling processing. We find that if (1) contrary to background, the object regions have the signature of discontinuity with their neighbor regions. (2) Each object concentrates relatively in a small region, which can be considered as a homogeneous compact region, our algorithm can achieve satisfactory detection performance.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nong Sang, Tianxu Zhang, and Guoyou Wang "Gray-scale morphology for small object detection", Proc. SPIE 2759, Signal and Data Processing of Small Targets 1996, (31 May 1996); https://doi.org/10.1117/12.241185
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Cited by 4 scholarly publications.
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KEYWORDS
Digital filtering

Image filtering

Binary data

Detection and tracking algorithms

Nonlinear filtering

Boron

Electronic filtering

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