Computer Vision for Label and Expiry Date Inspection on Bottles
In the pharmaceutical industry, quality control is not just a matter of production efficiency, but a critical requirement for safety, regulatory compliance, and patient protection.
Seemingly minor errors—such as an incorrect label or an unreadable expiration date—can lead to serious consequences: product recalls, regulatory penalties, reputational damage, and health risks.
In this context, Computer Vision and Artificial Intelligence (AI Vision) technologies are becoming a strategic ally to automate and strengthen quality inspections on bottles, vials, and pharmaceutical containers.
The challenges of traditional quality control
Label and expiry date inspection has traditionally relied on:
manual checks,
sample-based inspections,
rule-based optical systems.
These approaches come with clear limitations:
human variability and visual fatigue,
difficulty detecting subtle defects at high production speeds,
poor adaptability to changes in layout, fonts, or materials,
high risk of false positives—or worse, false negatives.
As production lines become faster and more complex, these limitations turn into real bottlenecks.
What AI Vision means for quality control
AI Vision combines Computer Vision with Deep Learning algorithms to analyze images intelligently, going beyond rigid, rule-based logic.
In pharmaceutical quality control, this means:
inspecting every bottle in real time,
interpreting visual information as an experienced operator would,
identifying anomalies, errors, and deviations from the standard.
The result is a continuous, objective, and repeatable inspection process, fully integrated into production workflows.
Automated label inspection
With AI Vision, it is possible to automatically verify:
label presence and correct positioning
alignment and orientation
consistency between label, batch, and product
graphic integrity (wrinkles, tears, bubbles)
correctness of texts, codes, and mandatory symbols
The system learns the correct reference model and flags even minimal deviations without slowing down the line.
Expiry date and batch code verification
One of the most critical aspects of pharmaceutical inspection is the control of expiry dates and batch numbers, often printed using different techniques and on challenging surfaces.
AI Vision enables manufacturers to:
read dates and codes even under variable lighting conditions,
verify presence and legibility,
cross-check information with production data,
detect printing defects, smudges, or missing information.
This dramatically reduces the risk of non-compliant products reaching the market.
Integration with quality systems
The real value of AI Vision emerges when it is integrated with MES and QMS systems.
Each detected anomaly can:
automatically generate a non-conformity record,
be linked to batch, line, and shift,
trigger real-time alerts for operators,
feed quality reports and KPIs.
This turns visual inspection into a fully digital quality and traceability ecosystem, rather than an isolated control step.
Tangible benefits for the pharma industry
Adopting AI Vision for label and expiry date inspection delivers measurable advantages:
significant reduction in errors and rework
stronger compliance with regulations and audits
100% inspection instead of sampling
more reliable and structured quality data
reduced operator stress and improved support on the line
All while maintaining the highest standards of product safety and integrity.
Conclusion
In the pharmaceutical industry—where accuracy and reliability are non-negotiable—AI Vision represents a natural evolution of quality control.
Automating label and expiry date inspection on bottles means protecting patients, companies, and brands, transforming visual inspection into an intelligent, integrated, and data-driven process.
Artificial Intelligence does not replace quality—it makes it measurable, scalable, and sustainable over time.
Want to know more'? Contact us at info@metalya.it