Evidence map›Paper›PMID 35069776›Full record

ArticleComputational and mathematical methods in medicine2022

Hand Gesture of Recognition Pattern Analysis by Image Treatment Techniques.

Khalid Twarish Alhamazani, Jalawi Alshudukhi, Saud Aljaloud, Solomon Abebaw

RetractedAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Retracted: Hand Gesture of Recognition Pattern Analysis by Image Treatment Techniques.Computational and mathematical methods in medicine · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Khalid Twarish AlhamazaniUniversity of Ha'il, College of Computer Science and Engineering, Department of Computer Science, Saudi Arabia.ORCID https://orcid.org/0000-0001-7195-4301
Jalawi AlshudukhiUniversity of Ha'il, College of Computer Science and Engineering, Department of Computer Science, Saudi Arabia.ORCID https://orcid.org/0000-0003-0619-0020
Saud AljaloudUniversity of Ha'il, College of Computer Science and Engineering, Department of Computer Science, Saudi Arabia.ORCID https://orcid.org/0000-0002-4700-1815
Solomon AbebawDepartment of Statistics, Mizan-Tepi University, Ethiopia.ORCID https://orcid.org/0000-0003-2911-2957

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The goal of this project is to write a program in the C++ language that can recognize motions made by a subject in front of a camera. To do this, in the first place, a sequence of distance images has been obtained using a depth camera. Later, these images are processed through a series of blocks into which the program has been divided; each of them will yield a numerical or logical result, which will be used later by the following blocks. The blocks into which the program has been divided are three; the first detects the subject's hands, the second detects if there has been movement (and therefore a gesture has been made), and the last detects the type of gesture that has been made accomplished. On the other hand, it intends to present to the reader three unique techniques for acquiring 3D images: stereovision, structured light, and flight time, in addition to exposing some of the most used techniques in image processing, such as morphology and segmentation.

Indexed as

GesturesUser-Computer InterfaceComputational BiologyHandHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMovementPattern Recognition, AutomatedVideo Recording

Identifiers

PMID35069776
PMCPMC8767380

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.