Evaluation of the Comprehensive Quality of Appearance Based on Machine Vision

Embroidered fabric is a type of cloth that undergoes dyeing and finishing after weaving, making it a crucial raw material for further textile and apparel production. The visual quality of embroidered fabric plays a significant role in the subsequent printing and garment manufacturing processes. Therefore, textile manufacturers focus on two main objectives when inspecting embroidered fabric: 1) Identifying the types and quantities of defects present in the fabric to assign appropriate quality scores. 2) Providing detailed information about the detected flaws so that inspectors can diagnose the issues and implement effective solutions to prevent similar problems from recurring. ![Image of embroidered fabric inspection](http://i.bosscdn.com/blog/wa/te/r_/201712290935407900.jpg) During the embroidery process, fabrics often develop various defects such as missing warp threads, missing weft threads, or oil stains. Traditionally, fabric quality assessment has relied heavily on manual inspections, where workers manually check the fabric offline. While this method helps maintain some level of quality control, it suffers from several drawbacks. Inspectors may become fatigued, leading to inefficiency and inconsistencies. Additionally, each person's interpretation of defects is subjective, and without a standardized approach, the results are not always reliable. This lack of consistency affects the overall quality of the fabric, which in turn impacts the profitability of the manufacturer and reduces the competitiveness of their products. ![Image of manual fabric inspection](http://i.bosscdn.com/blog/wa/te/r_/201712290935538784.jpg) **Manual Inspection vs. Machine Vision-Based Fabric Inspection** To overcome these challenges, modern technology has introduced machine vision systems that combine human visual inspection principles with advanced automation. These systems offer a more reliable, objective, and consistent way to evaluate the appearance of fabrics. They can detect defects both during the production process (online) and after it is completed (offline), ensuring that only high-quality products reach the market. ![Image of machine vision system](http://i.bosscdn.com/blog/wa/te/r_/201712290936029420.jpg) Xi'an Kede has extensive experience in industrial vision technology and has successfully applied it in textile factory inspections. Their systems have effectively addressed the challenge of detecting surface defects in textiles and glass fiber fabrics. By implementing these technologies, factories can significantly reduce labor costs while improving product quality and gaining a stronger competitive edge in the market.

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