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- Title
Observation of Animal and Plant Microstructure Based on Computer Vision.
- Authors
Xie Jingwei; Li Huiyi
- Abstract
Microscopic observation and counting of plant cells play an important role in many fields such as botanical images. The traditional manual counting method is inefficient, time-consuming and low accuracy. At present, the research of automatic cell counting by image processing technology is mostly a few cell adhesion, cell shape integrity and size uniformity. In fact, most of the cell images are irregular, uneven and conglutinated. In this paper, double threshold detection algorithm is used to segment and count the adherent cells. The accuracy of the algorithm is high, which can meet the actual experimental requirements. The threshold set in this paper can be considered to add other sample characteristics, and the appropriate threshold can be obtained by training different cell samples. In order to improve the accuracy, the classification algorithm was used to classify the adherent cells. In addition, cell segmentation algorithm can be based on edge detection, threshold and region algorithm to get more adaptive segmentation algorithm. It has certain reference value for the observation of plant microstructure.
- Subjects
PLANT cells &; tissue analysis; BOTANICAL microscopy; CYTOMETRY; CLASSIFICATION algorithms; MICROSTRUCTURE
- Publication
Acta Microscopica, 2020, Vol 29, Issue 2, p965
- ISSN
0798-4545
- Publication type
Article