Food and pharmaceuticals directly affect human life and health, making even a 0.1% defect absolutely unacceptable in the industry. If drug quality issues threaten people's safety, it could lead to catastrophic consequences. Tasks such as rapid, precise measurement of tiny dimensions, shape matching, and color identification are impossible for the human eye to perform consistently over time, and conventional physical sensors also struggle to handle them effectively. Therefore, pharmaceutical companies—especially internationally renowned leading manufacturers—place extremely high importance on every stage of drug production, including the later packaging processes.

Drug shortage or bottle shortage detection
As the regulations in the pharmaceutical industry continue to tighten, the quality standards for pharmaceutical packaging have become increasingly strict. After the drug particles are sealed in the blister, the manufacturer must ensure that all the drug particles in each blister are intact; for bottled drugs, when several bottles are packed into a larger outer package for shipment, the enterprise must ensure that there are no missing bottles in each large package to avoid such issues affecting its own brand reputation.

Solution: By using the machine vision method, it is possible to quickly and accurately determine whether the inspected object is intact. First, we set up the image sensor to collect the product images after packaging is completed. Then, using the pre-set area parameters, we conduct individual inspections and comparisons for each pill and each bottle of medicine. In this way, damaged pills and incomplete packaging will be accurately detected, while qualified products will be released normally.

Bottle mouth damage detection
For liquid medicine bottles, after being canned, it is necessary to determine whether the bottle mouth is damaged. This is related to whether glass fragments will be mixed into the medicine liquid.

Solution:
1. Install the image sensor after the drug liquid filling process. With the help of the graphic matching tool, it can determine whether the bottle mouth is damaged.
2. Before the formal detection begins, the image sensor will first record the standard features of a normal bottle mouth as the comparison benchmark for subsequent detection.
3. When the filled drug bottles pass in front of the lens, the sensor will capture the real-time image of the current bottle mouth and compare it with the pre-stored standard features. Once it detects inconsistency, it will send a signal, causing the rejection mechanism to remove this unqualified drug bottle from the production line.
4. Users can set the similarity degree based on the bottle mouth features through the visual software. Assuming a setting of 90%, that means the sensor will only consider the bottle mouth of the detected bottle as intact when the similarity degree between the detected feature and the sensor's memory feature reaches 90% or above. After this detection, all drug bottles with damaged bottle mouths can be removed.

Machine Vision Inspection
In the manufacturing process of pharmaceuticals, even the slightest error is not allowed. Therefore, pharmaceutical enterprises are constantly developing increasingly mature machine vision systems to avoid quality issues. With the continuous increase in the importance of safety in drugs and medical devices, more and more manufacturers are introducing machine vision technology into actual production to achieve the goals of improving production efficiency and strengthening product quality assurance.