Evidence map›Paper›PMID 37236974›Full record

ArticleScientific reports2023

Estimation of drinking water volume of laboratory animals based on image processing.

Zhihai Liu, Feiyi Liu, Qingliang Zeng, Xiang Yin, Yang Yang

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhihai LiuCollege of Transportation, Shandong University of Science and Technology, Qingdao, 266590, China.
Feiyi LiuCollege of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, 266590, China.
Qingliang ZengCollege of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, 266590, China.
Xiang YinCollege of Transportation, Shandong University of Science and Technology, Qingdao, 266590, China.
Yang YangCollege of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao, 266590, China. yang.yang@sdust.edu.cn.

Funding

National Key Research and Development Program of China grant number 2019GGX104048the projects of the Shandong Provincial Key Research and Development Project grant number 2019SDZY01
6 · The paper itself

Abstract

This paper describes an image processing-based technique used to measure the volume of residual water in the drinking water bottle for the laboratory mouse. This technique uses a camera to capture the bottle's image and then processes the image to calculate the volume of water in the bottle. Firstly, the Grabcut method separates the foreground and background to avoid the influence of background on image feature extraction. Then Canny operator was used to detect the edge of the water bottle and the edge of the liquid surface. The cumulative probability Hough detection identified the water bottle edge line segment and the liquid surface line segment from the edge image. Finally, the spatial coordinate system is constructed, and the length of each line segment on the water bottle is calculated by using plane analytical geometry. Then the volume of water is calculated. By comparing image processing time, the pixel number of liquid level, and other indexes, the optimal illuminance and water bottle color were obtained. The experimental results show that the average deviation rate of this method is less than 5%, which significantly improves the accuracy and efficiency of measurement compared with traditional manual measurement.

Identifiers

PMID37236974
PMCPMC10219945

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.