The application of machine vision in the medical field has expanded from traditional visual inspections of pharmaceutical packaging, bottles, and labels to include the detection of biological chips and radiography in radiology. By introducing machine vision systems, the collection, storage, management, processing, and transmission of image information can be effectively achieved.

1. Detection of Missing Medication or Bottles using Machine Vision

Solution: By leveraging the techniques of machine vision, objects can be quickly and accurately inspected for integrity. By setting up image sensors to capture images of packaged objects, a comparison can be made against predefined area parameters for each medication particle or bottle. In this way, damaged medication particles or packaging with missing bottles can be detected, ensuring that only properly packaged items proceed further.

2. Detection of Bottle Mouth Damage using Machine Vision

Solution: After the process of filling the liquid medication into bottles, image sensors can be installed to inspect the bottle mouth for any signs of damage. Prior to inspection, the image sensor records the normal characteristics of the bottle mouth. As the filled bottles pass in front of the sensor lens, the sensor captures the current characteristics of the bottle mouth and compares them with the recorded ones. Any discrepancies trigger the sensor to emit a signal, leading to the rejection of the respective bottle. Users can set a similarity threshold in the vision software to determine the acceptable level of similarity between the detected bottle mouth characteristics and the recorded ones. By implementing this inspection, all bottles with damaged mouths can be effectively removed from the production line.

Application Areas: Detection of pharmaceutical appearance defects, packaging defects, visible foreign particles, and sealing defects in injection and infusion products, as well as the detection of label misprinting, missing labels, inkjet printing defects, and label misalignment.

Keywords:

1. Machine vision application

2. Detection of missing medication or bottles

3. Detection of bottle mouth damage

4. Pharmaceutical appearance defect detection

5. Label misprinting, missing labels, inkjet printing defects, and label misalignment detection.