Bulletin of
Vitebsk State
Technological
University

Abstract

Despite many years of automation experience, the final inspection stage has not yet been digitized. At sewing enterprises, traditionally, the detection of defects in batches of finished clothes is carried out by contact method by the employees of the technical control department.

The aim of the study is to develop a method for recognizing technological and design defects that reduce the grade of products for remote monitoring of the quality of sewing semi-finished products and finished products using a computer vision software- and-hardware complex.

An analysis of the existing methods for identifying visual information has shown that to achieve the task, the Haar cascade classifier can be used, which makes it possible to recognize scanned objects with a high degree of reliability by comparing the characteristics of images with templates.

The authors have developed the GarmentScanner software and hardware system, which reads visual information using machine vision, classifies it using the Viola/Jones algorithm based on the calculation of the total brightness of pixels in arbitrary rectangular areas, and performs metric actions. At the current stage of the study, the GarmentScanner software works with photographic images of finished products of flat shapes (t-shirts, shorts). The following attributes were selected as the tested attributes: the coordinates of the base and reference points on the product (in accordance with the model features); the symmetry of the contour; the conformity of the dimensions of a particular model to the reference sample (according to the table of measures). Approbation of GarmentScanner work is carried out at outsourcing sewing enterprises in China, cooperating with Russian design agencies. An additional effect from the use of GarmentScanner was the reduction of conflict situations in production, arising against the background of different interpretations by customers from Russia and outsourcing contractors of the concept of "production quality and its rejection".

Machine Vision Digital Technology for Non-Contact Quality Control of Garment Manufacturing