Character Flaw Detection of Inkjet Coding on Food Packaging: From Missed Detection to Stable Recognition

In the food packaging industry, inkjet coding is almost the “ID card” of every product before it leaves the factory.
Production date, batch number, traceability information… These seemingly insignificant characters are often difficult to be detected manually in a timely manner on the production line. Once problems such as missing coding, duplicate coding, and character missing occur, they will not only affect product compliance, but also directly lead to consumer complaints and brand risks.

Inspection Background

When it comes to specific production lines, the detection of inkjet coding on bottle caps is far from simple as imagined.
Traditional bottle caps are mostly made of high-reflection plastic material, with curvature and texture changes on the surface, so the coding area is extremely susceptible to reflection interference. On the other hand, in the process of high-speed continuous production, the coding equipment is also affected by factors such as temperature and humidity, and nozzle status, which is prone to abnormal situations such as character broken lines, ink diffusion, coding offset, and ghosting, making it difficult to meet the current demand for high-speed and high-consistency quality inspection in the food packaging industry.

Therefore, how to achieve stable imaging and accurate identification of inkjet coding characters in a high-speed operation and complex reflection environment has become a key difficulty in bottle cap coding detection.
Based on the above challenges and combined with actual production line requirements, the readability and recognition reliability of inkjet coding characters under complex working conditions can be improved by optimizing the optical imaging and visual inspection solution.

Inspection Requirements

Inspection Object: Milk Bottle Cap
Inspection Type: OCR Character Flaw Detection
Field of View (FOV): 4×4cm
Pixel Accuracy: 16μm

Inspection Solution

Camera: Do3think 5MP Monochrome Area Scan Industrial Camera MGV518M-H2
Lens: 25mm Lens
Light Source: Ring Light

Deployment Schematic

Imaging Effect

Solution Description

In response to the above problems, this solution sets the inspection field of view to about 4×4cm in the imaging design, and requires the system to have a pixel resolution capability of about 16μm, so as to meet the demand for stable recognition of the details of inkjet coding characters.

Under this imaging condition, the required number of pixels is calculated inversely according to the pixel accuracy: the 4cm field of view corresponds to a range of about 40000μm, and with an accuracy of 16μm, at least about 2500 effective pixels are required in a single direction.

Combined with the need to reserve a certain amount of imaging redundancy for anti-jitter, edge compensation and algorithm cropping in actual industrial applications, this solution finally selects the Do3think MGV518M-H2 area scan camera with a resolution of 2448×2048. This industrial camera has a pixel size of 3.4μm×3.4μm, with higher sensitivity and clearer imaging details.

It is matched with a 25mm lens and a high-uniformity ring light source. By optimizing the irradiation angle of the light source and imaging parameters, the reflection interference on the surface of the bottle cap is effectively reduced, the grayscale contrast between the inkjet coding characters and the background is further enhanced, and the character outline is made clearer and more stable.

It effectively solves the common flaw detection problems of bottle cap coding in the food packaging industry, such as character blur, missing coding, duplicate coding and misalignment caused by high reflection, ink diffusion, nozzle offset, etc., helps to improve detection accuracy and operation efficiency, and is suitable for conventional coding detection and character recognition scenarios.