Open AccessA Survey of Water Droplet Recognition Algorithms on Object Surface
Author(s) -
Zheng Yingya,
Zan Xiangzhen
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1605/1/012039
Subject(s) - segmentation , cluster analysis , object (grammar) , computer science , artificial intelligence , enhanced data rates for gsm evolution , image segmentation , pattern recognition (psychology) , cognitive neuroscience of visual object recognition , surface (topology) , segmentation based object categorization , current (fluid) , scale space segmentation , algorithm , value (mathematics) , mathematical morphology , computer vision , image (mathematics) , machine learning , mathematics , image processing , engineering , geometry , electrical engineering
The recognition and extraction of water droplets on object surface have important practical application value. This article focuses on summarizing the different water droplet recognition segmentation algorithms, mainly based on threshold, edge detection, region and morphology segmentation, and clustering and special model-based segmentation algorithms. Then, some shortcomings of the current algorithms are analyzed and the future research direction is prospected.