Evidence map›Paper›PMID 35665278›Full record

ArticleComputational intelligence and neuroscience2022

The Computer-Aided Design Algorithm of Dyeing and Weaving Graphics from the Perspective of Public Art.

Yan Cui

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational intelligence and neuroscience, 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 It has been retracted, and should not be counted.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
0.4field-weighted citation impact, top 35% of its field
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 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Yan CuiFashion Art Design Department, Hubei Academy of Fine Arts, Wuhan, China.ORCID https://orcid.org/0000-0002-0074-7580
Hubei Institute of Fine Arts · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the acceleration of economic development, people put forward higher requirements for clothing style. In this context, the application of traditional patterns has good artistic effects, can show a unique style, and can also express the artistic beauty of clothing through deformation, color distribution, and other forms, and occupies a relatively large position in the design process of dyeing and weaving art. Aiming at the problem of inaccurate extraction of image information from known visual scenes in the original art-aided design, resulting in unclear output images, this paper proposes a computer-aided design algorithm for dyeing and weaving graphics in the field of public art by color segmentation of the known visual scene images according to the set threshold, morphological processing of the segmented images, reducing noise and fractures affecting the acquired connected areas, and formulating extraction rules to screen candidate areas. Furthermore, dense sampling form is used to extract more scale invariant feature transform (SIFT) target features in the candidate area, match the feature points, integrate the coordinate system of known image information into a unified coordinate system, output the design image, and complete the auxiliary design of dyeing and weaving graphics. The results of simulation experiments show that the computer-aided design algorithm of dyeing and weaving graphics in the public art field is more accurate than the original method in extracting information from known images, which helps to solve the problem of clear output dyeing and weaving images, and improves the quality of dyeing and weaving images.

Indexed as

AlgorithmsColoring AgentsComputer-Aided DesignComputer SimulationHumansImage Processing, Computer-AssistedColoring Agents

Identifiers

PMID35665278
PMCPMC9159859
OpenAlexW4281556967

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.