CN-122020026-A - Clothing aging prediction method, system, equipment and storage medium

CN122020026ACN 122020026 ACN122020026 ACN 122020026ACN-122020026-A

Abstract

The invention discloses a clothing aging prediction method, a system, equipment and a storage medium, and belongs to the technical field of clothing detection. According to the method, the device and the system, the aging image data of the clothing to be predicted are acquired, the aging image data are acquired after the aging step is executed, the aging characteristic data are determined according to the aging image data and the type data of the clothing to be predicted, the service life of the clothing to be predicted is predicted according to the aging characteristic data, and the technical effect of improving the accuracy of the prediction of the service life of the clothing is achieved.

Inventors

HUANG XIAOLING
HUANG NA
ZHANG ZHENZHU
CAI WEIQI
LI HUISHAN
WU ZHIXUAN

Assignees

中联品检(佛山)检验技术有限公司

Dates

Publication Date: 20260512
Application Date: 20260108

Claims (10)

1. A method for predicting garment aging, the method comprising the steps of: Acquiring aging image data of a garment to be predicted, wherein the aging image data is acquired after an aging step is executed on the garment to be predicted; Determining aging characteristic data according to the aging image data and the type data of the clothing to be predicted; And predicting the service life of the garment to be predicted according to the aging characteristic data.
2. The garment aging prediction method according to claim 1, wherein the step of determining aging characteristic data from the aging image data and the type data of the garment to be predicted comprises: Determining a plurality of garment analysis areas according to the aging image data and the garment type; determining area characteristic data according to each clothing analysis area and the aging image data, wherein the clothing analysis areas correspond to the area characteristic data one by one; correcting a plurality of the regional characteristic data according to the aging process data; And determining the aging characteristic data according to a plurality of the regional characteristic data.
3. The garment aging prediction method of claim 2, wherein the determining region characteristic data from each of the garment analysis region and the aging image data comprises: Extracting target data in the aging image data according to the clothing analysis area to obtain each target data; Determining corresponding morphological change characteristic data, color change characteristic data and surface quality change characteristic data according to each target data; and determining regional characteristic data according to the morphological change characteristic data, the color change characteristic data and the surface quality change characteristic data corresponding to each target data, and obtaining a plurality of regional characteristic data.
4. The method of claim 3, wherein the step of determining corresponding morphological change feature data, color change feature data, and surface quality change feature data from each of the target data comprises: Extracting edge data of the target data according to an edge extraction algorithm, and counting the number of pixels in the target data; Determining the morphological change characteristic data according to the edge data, the pixel number and preset morphological data of the clothing to be predicted; Counting the color data of the target data, and determining the color change characteristic data according to the color data and preset social color data of the clothing to be predicted; And determining the surface quality change characteristic data according to a texture analysis algorithm and the target data.
5. The garment aging prediction method according to claim 1, wherein the step of predicting the service life of the garment to be predicted from the aging characteristic data comprises: Determining an aging degree score according to the aging characteristic data and a preset aging model; and predicting the service life according to the ageing degree score and the ageing threshold value.
6. The method of claim 5, wherein the aging characteristic data comprises morphological change characteristic data, color change characteristic data, and surface quality change characteristic data, the predetermined aging model comprises a weight value corresponding to each characteristic type, and the step of determining the aging degree score according to the aging characteristic data and the predetermined aging model comprises: weighting calculation is carried out according to the morphological change characteristic data, the color change characteristic data, the surface quality change characteristic data and the weight value corresponding to each characteristic type, and a first aging degree score of each clothing analysis area is determined; calculating an average aging degree score from the plurality of first aging degree scores; And taking the average ageing degree score as the ageing degree score.
7. The clothing aging prediction method according to any one of claims 1 to 6, wherein the step of acquiring aging image data of the clothing to be predicted includes: the clothing to be predicted is arranged in an environment simulation device, wherein the environment simulated by the environment simulation device comprises at least one of a washing circulation environment, a friction and wear environment, a preset sunlight environment and a preset humidity environment; Controlling an environment simulation device to simulate an aging environment; And controlling an image acquisition device to acquire the aging image data of the garment to be predicted.
8. A garment aging prediction system, the garment aging prediction system comprising: The device comprises an acquisition module, a prediction module and a prediction module, wherein the acquisition module is used for acquiring aging image data of the clothing to be predicted, wherein the aging image data is acquired after the aging step is executed on the clothing to be predicted; the analysis module is used for determining aging characteristic data according to the aging image data and the type data of the clothing to be predicted; And the prediction module is used for predicting the service life of the garment to be predicted according to the ageing characteristic data.
9. A garment aging prediction device comprising a memory, a processor and a garment aging prediction program stored on the memory and executable on the processor, the garment aging prediction program configured to implement the steps of the garment aging prediction method of any one of claims 1 to 7.
10. A storage medium having stored thereon a garment aging prediction program which when executed by a processor performs the steps of the garment aging prediction method of any one of claims 1 to 7.

Description

Clothing aging prediction method, system, equipment and storage medium Technical Field The present invention relates to the field of clothing detection, and in particular, to a method, a system, an apparatus, and a storage medium for predicting clothing aging. Background Along with the continuous improvement of the requirements of clothing manufacture, the service life of the clothing directly influences product quality evaluation and product pricing, and the traditional aging evaluation method mainly relies on manual observation, so that the aging index with strong subjectivity and incapability of effectively setting a standard often exists in the manual observation mode, and therefore, the aging test is inaccurate. The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art. Disclosure of Invention The invention mainly aims to provide a clothes aging prediction method, a system, equipment and a storage medium, which aim to effectively improve the accuracy of clothes service life prediction. In order to achieve the above object, the present invention provides a clothing aging prediction method, which includes the steps of: Acquiring aging image data of a garment to be predicted, wherein the aging image data is acquired after an aging step is executed on the garment to be predicted; Determining aging characteristic data according to the aging image data and the type data of the clothing to be predicted; And predicting the service life of the garment to be predicted according to the aging characteristic data. Optionally, the step of determining aging characteristic data according to the aging image data and the type data of the garment to be predicted includes: Determining a plurality of garment analysis areas according to the aging image data and the garment type; determining area characteristic data according to each clothing analysis area and the aging image data, wherein the clothing analysis areas correspond to the area characteristic data one by one; correcting a plurality of the regional characteristic data according to the aging process data; And determining the aging characteristic data according to a plurality of the regional characteristic data. Optionally, the step of determining region feature data from each of the garment analysis region and the aging image data comprises: Extracting target data in the aging image data according to the clothing analysis area to obtain each target data; Determining corresponding morphological change characteristic data, color change characteristic data and surface quality change characteristic data according to each target data; and determining regional characteristic data according to the morphological change characteristic data, the color change characteristic data and the surface quality change characteristic data corresponding to each target data, and obtaining a plurality of regional characteristic data. Optionally, the step of determining the corresponding morphological change feature data, color change feature data, and surface quality change feature data according to each of the target data includes: Extracting edge data of the target data according to an edge extraction algorithm, and counting the number of pixels in the target data; Determining the morphological change characteristic data according to the edge data, the pixel number and preset morphological data of the clothing to be predicted; Counting the color data of the target data, and determining the color change characteristic data according to the color data and preset social color data of the clothing to be predicted; And determining the surface quality change characteristic data according to a texture analysis algorithm and the target data. Optionally, the step of predicting the service life of the garment to be predicted according to the aging characteristic data includes: Determining an aging degree score according to the aging characteristic data and a preset aging model; and predicting the service life according to the ageing degree score and the ageing threshold value. Optionally, the aging characteristic data comprises morphological change characteristic data, color change characteristic data and surface quality change characteristic data, the preset aging model comprises a weight value corresponding to each characteristic type, and the step of determining the aging degree score according to the aging characteristic data and the preset aging model comprises the following steps: weighting calculation is carried out according to the morphological change characteristic data, the color change characteristic data, the surface quality change characteristic data and the weight value corresponding to each characteristic type, and a first aging degree score of each clothing analysis area is determined; calculating an average aging degree score from