Grayscale Morphology is a morphological image processing framework that extends binary morphological operations to grayscale images by interpreting pixel intensities as topographic surface heights, thereby enabling structuring element-based probing of image shape and texture through operations such as dilation, erosion, opening, and closing.
225
Publications
15.6K
Citations
553
Authors
269
Institutions
Publications per year
2017–2026
29
Parents
Publications
225
Optical Identification of Single‐ and Few‐Layer MoS<sub>2</sub> Sheets
Hai Li, Gang Lü, Zongyou Yin et al. · Small · 2012 · 321 citations
Natural Sciences, Materials Engineering, Materials Science +17
1–5 of 225
Authors
553
- ER
8
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- FY
6
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- LV
6
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5
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4
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1–5 of 553
Institutions
269
Rochester Institute of Technology
Rochester, United States
8 h-index
10 publications
187 citations
Centre National de la Recherche Scientifique
Paris, France
7 h-index
22 publications
4.8K citations
Xerox (United States)
Norwalk, United States
5 h-index
5 publications
2.1K citations
New Jersey Institute of Technology
Newark, United States
5 h-index
8 publications
289 citations
Indian Statistical Institute
Kolkata, India
5 h-index
6 publications
437 citations
University of Groningen
Groningen, The Netherlands
4 h-index
8 publications
837 citations
University of Maryland, College Park
College Park, United States
4 h-index
9 publications
399 citations
The University of Texas at Arlington
Arlington, United States
4 h-index
5 publications
560 citations
1–8 of 269
Venues
- IEEE Transactions on Pattern Analysis and Machine Intelligence
TPAMI · 15 publications · 4.1K citations
14
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- IEEE Transactions on Image Processing
16 publications · 2.8K citations
13
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- Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE
22 publications · 408 citations
13
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- Pattern Recognition
8 publications · 533 citations
8
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- Pattern Recognition Letters
6 publications · 146 citations
6
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