Line Scan Camera Light Source Selection and Illumination Methods

In machine vision, the selection of light sources and illumination methods is also very important. The appropriate choice of light sources and illumination methods can effectively help line scan cameras capture clear images, greatly improving recognition accuracy. The following content introduces the selection of light sources and illumination methods for line scan cameras.

Line Scan Camera Light Source Selection

In line scanning projects, commonly used light sources include LED light sources, halogen lamps (fiber optic light sources), and high-frequency fluorescent lamps.
LED light sources are currently the mainstream machine vision light sources. They are characterized by long life, good stability, and very low power consumption.

Halogen lamps, also known as fiber optic light sources, are particularly bright, but their downside is obvious—they have a short life, only 1000-2000 hours or so, and require frequent replacement of bulbs. The light source is a halogen bulb, which, through a special optical lens and a light distribution system, is finally output through a fiber optic cable. The light source power is very high, up to 250 watts. Halogen lamps also have another name—cold light sources—because after transmission through the fiber optic cable, the end that emits light is not hot and has stable color temperature, making them suitable for occasions where the environment temperature is sensitive.

High-frequency fluorescent lamps have a similar light-emitting principle to fluorescent lights, except that the lamps are industrial-grade products. They are suitable for large-area illumination, have high brightness, and low cost, but the biggest drawback of fluorescent lamps is flicker and rapid decay. Fluorescent lamps definitely require a high-frequency power supply, meaning the frequency of light source flicker is much higher than the frequency of camera image acquisition (for line-scan cameras, this is the line scanning frequency) to eliminate flicker in the image. A dedicated high-frequency power supply can achieve 60KHz.

The Three Illumination Methods for Line Scan Cameras

Bright Field Illumination

Bright field illumination is the standard method for surface inspection using a linear scanning camera. The arrangement of the camera and illumination equipment should place the camera in the reflection angle of the illumination device (the angle of incidence = the angle of reflection).
In this way, as much incident light as possible can be detected. This is particularly effective for reflective materials. Bright areas appear bright, and dark areas appear dark. If the surface structures are angled and not aligned but tilted, they will also appear very dark in the camera image. Surface scratches or inclined phases will have darker gray shadows in the image.

Dark Field Illumination

Line-scan cameras can also be used to achieve a dark field effect. Therefore, the illumination does not aim at the component from the reflection angle but is significantly more oblique. Directly reflected light does not enter the camera, so the field appears very dark, and the camera can only detect faint stray light. This technique requires a lot of light. Scratches, gaps, elevations, or embossing appear bright under scattered light due to their uneven surfaces. Detecting smooth surfaces can be challenging.

Backlighting

Under these lighting conditions, the camera and illumination are directly opposite each other, with the test object in between them. This allows the contours of opaque materials to be seen, detecting edge breaks, and measuring components. Transparent objects (such as glass, metal foil, etc.) can be used to make bubbles, cracks, or edge fragments within the material visible.

The type of light source and illumination method used depends on specific application requirements, including the material properties of the object being inspected, surface conditions, inspection distance, and image quality requirements. The correct selection of light sources and illumination methods greatly assists in enhancing the detection quality and precision of machine vision systems.