Machine vision systems excel at inspecting bottle and vial features including label quality, print readability, fill levels, and container defects such as chips or cracks. However, a more complex challenge lies in detecting contents inside these containers is accurately identifying the pills themselves. This article explores how combining machine vision with Raman spectroscopy addresses this limitation by enabling non-contact inspection of internal pill identification.

The Synergy of Advanced Technologies

The integration of Raman spectroscopy and advanced imaging techniques enables detailed analysis from within vials, extending beyond typical label-based inspections to include pill strength classification. Centice’s Pass Rx system combines these technologies to achieve high-accuracy pharmaceutical authentication through sophisticated image accumulation methods across multiple light modes and spectral bands.

Technical Challenges in Pharmaceutical Vial Inspection

Inspecting semi-transparent vials requires overcoming several technical hurdles:

  • Limited Light Transmission: Amber glass blocks certain wavelengths, especially blue spectra.
  • Physical Constraints: The system must be compact enough to fit on a pharmacy counter while maintaining sufficient space for supporting equipment.
  • Visual Distortions: Short focal distances and stacking effects create complex imaging challenges.

Advanced Image Accumulation Techniques

To maximize discriminative information from multi-spectral imaging, the Pass Rx employs image accumulation across multiple light modes and spectra. This methodology enhances object discrimination by combining data from different illumination conditions. The compact design required collaboration with partners like The Imaging Source for camera selection and Navitar to develop specialized lenses minimizing fisheye effects.

Evaluating Shape and Size Features

Shape analysis is categorized into two approaches: predominant shape detection without prior knowledge, or using expected shapes provided by spectroscopy. Predominant shape extraction relies on segmenting pixels associated with objects inside the vial rather than external elements. Figure 3 demonstrates circle-based pill identification methods. Circle pills

When spectral data is insufficient for precise categorization, known shape/size sets can be directly passed to the vision system. This method effectively confirms shapes but uses computationally intensive techniques—see Figures 4 and 5 comparing diamond-shaped pill recognition.

Color Evaluation Challenges

Color analysis requires careful calibration accounting for vial material spectra blocking certain light wavelengths (blue in amber vials). Identifying valid color pixels involves marking non-informative areas to improve histogram comparison. Figure 6 highlights invalid color regions, while the original image appears in Figure 7. Invalid color pixels Original image

The integration of Raman Spectroscopy and machine vision creates powerful synergies for pharmaceutical authentication through advanced object classification techniques not achievable with either technology alone. This synergy addresses limitations inherent to traditional inspection methods, which typically focus on surface-level features like labels or fill levels.

Key Technical Components

  • Lighting and Sensitivity: Centice partnered with imaging partners to develop a multi-spectral lighting system.
  • Hardware Partnerships: Collaboration resulted in compact cameras and lenses minimizing fisheye distortion while meeting stringent performance requirements within limited spaces.

Last Updated: 2025-09-05 01:39:33