Frequently Asked Questions

Machine vision is a technology that uses industrial cameras, lenses, lighting, and image processing software to automatically capture and analyse images for inspection, measurement, and guidance. It enables manufacturers to improve product quality, increase production efficiency, and reduce human error by performing tasks that would be difficult or inconsistent with manual inspection.

Area scan and line scan cameras are two fundamental types of imaging technologies used in machine vision systems. Area scan cameras capture a complete image in a single exposure, making them suitable for applications where the entire object can be viewed at once. In contrast, line scan cameras capture images one line at a time and build a complete image as the object moves past the camera, which makes them particularly effective for continuous or high-speed inspection processes.

A line scan camera should be used when inspecting continuous materials such as paper, film, textiles, or metal, or when very high-speed imaging is required. It is also the preferred choice when inspecting large objects that cannot fit within a single field of view, as it allows for seamless image construction with consistent resolution across the entire scan width.

An area scan camera is best suited for applications where objects are stationary or can be stopped momentarily for inspection. It is commonly used in applications such as presence detection, assembly verification, and general quality inspection, where simplicity of setup and lower system complexity are important considerations.

The choice depends on application requirements. Smart cameras are ideal for compact, self-contained solutions with moderate complexity. Board cameras are suited to embedded OEM designs where integration and size are critical. Industrial cameras provide the highest level of performance and flexibility for demanding machine vision systems.

The required resolution depends on the size of the smallest feature that needs to be detected or measured. As a general guideline, it is recommended that each critical feature is represented by at least two to four pixels to ensure reliable detection and measurement accuracy.

A board-level camera is a compact imaging module consisting of a bare PCB with an integrated image sensor and interface, designed for direct integration into embedded systems. Unlike enclosed industrial cameras, board cameras prioritise minimal size, low power consumption, and system-level customisation.

Board cameras are typically used when space constraints, weight limitations, or cost sensitivity are critical design factors. They are well suited to embedded vision applications such as robotics, kiosks, medical devices, and OEM systems, where the camera is integrated directly into the final product rather than deployed as a standalone unit.

Board cameras commonly use interfaces such as MIPI CSI-2, USB, or LVDS, depending on bandwidth and integration requirements. MIPI CSI-2 is widely used in embedded systems due to its high data throughput and low power consumption, while USB-based solutions offer easier integration with standard computing platforms.

Board cameras typically lack the mechanical robustness, environmental protection (e.g. IP-rated housings), and standardised mounting options of industrial cameras. They may also have limited support for larger sensors, advanced triggering, and deterministic data transfer, which can restrict their use in high-precision or high-speed industrial inspection systems.

A barcode reader is an imaging or laser-based device designed to decode 1D and 2D codes, such as QR codes and Data Matrix symbols, within an automated process. In machine vision systems, image-based barcode readers are commonly used due to their flexibility and ability to handle variable code quality and orientation.

Laser barcode scanners use a moving laser beam to detect reflected light patterns and are typically limited to 1D codes. Image-based readers, on the other hand, capture a full image using a camera sensor and decode both 1D and 2D codes, offering greater robustness in handling damaged, low-contrast, or poorly printed codes.

Barcode reading performance depends on several factors, including code quality, contrast, print resolution, lighting conditions, and the angle and distance between the reader and the code. Motion, surface reflectivity, and environmental conditions can also significantly impact decoding reliability.

Yes, high-performance barcode readers are designed to decode codes on fast-moving objects by combining high frame rates, short exposure times, and optimised decoding algorithms. Proper lighting and synchronisation are essential to ensure reliable performance in high-speed applications.

A full vision system is typically used when barcode reading is only one part of a broader inspection task, such as verifying code presence, position, or quality alongside other features. This allows a single system to perform multiple inspection functions, reducing hardware complexity and system cost.

A smart camera is a self-contained vision system that integrates an image sensor, processing unit, and vision software within a single device. It is designed to perform image acquisition and analysis onboard, eliminating the need for an external PC in many applications.

Smart cameras perform image processing internally using embedded processors, which simplifies system architecture and reduces hardware requirements. In contrast, PC-based systems offer greater processing power, flexibility, and scalability, making them more suitable for complex or computationally intensive applications.

Smart cameras are best suited to applications with well-defined inspection tasks, moderate processing requirements, and limited system complexity. They are commonly used in presence/absence detection, basic measurement, and code reading applications where ease of deployment and compact design are important.

Smart cameras are typically constrained by processing power, memory, and expandability. They may not be suitable for high-resolution imaging, multi-camera systems, or applications requiring advanced algorithms such as deep learning or high-speed data processing.

Smart cameras offer faster deployment and reduced system complexity but are generally less flexible and scalable than modular systems. Industrial camera systems, combined with external processing, provide higher performance, greater configurability, and better suitability for complex or high-speed applications.

Yes, it is possible to use an M12 lens on a C-mount camera by using a mechanical adapter; however, this approach introduces several limitations. M12 lenses are typically designed for smaller sensors, so when used with larger C-mount sensors, issues such as vignetting, reduced image quality, and poor edge resolution are common.

Additionally, M12 lenses are not optimised for the flange distance or optical requirements of C-mount systems, which can make achieving consistent focus and alignment more challenging. While this combination may be acceptable for non-critical or cost-sensitive applications, it is generally not recommended for precision machine vision tasks.

M12 lenses are best suited to applications where size, weight, and cost are the primary constraints, such as embedded vision systems, compact devices, or high-volume OEM designs. They are typically used with small sensors and in applications where moderate image quality is sufficient.

In contrast, C-mount lenses should be used when image quality, measurement accuracy, and system robustness are important, particularly in industrial inspection or high-resolution imaging. The choice ultimately depends on whether the application prioritises compact integration or optical performance.

Lens selection is a critical factor in any machine vision system, as it directly affects image quality, accuracy, and consistency. A properly selected lens ensures that the required field of view is achieved while maintaining sharp focus and minimal distortion, which is especially important in precision measurement and inspection applications.

Backlighting involves placing the light source behind the object relative to the camera, creating a high-contrast silhouette. It is commonly used for dimensional measurement, edge detection, and presence/absence inspection where precise object boundaries are required.

Coaxial illumination introduces light along the same optical axis as the camera using a beam splitter, providing uniform illumination of flat, reflective surfaces. It is particularly effective for detecting features on specular objects such as polished metals or glass.

The wavelength of the light affects how it interacts with the material being inspected. Different wavelengths can enhance or suppress specific features, such as using infrared for penetration or ultraviolet for surface detail. Selection of wavelength is often used to improve contrast and reduce interference from ambient light.

Lighting uniformity is influenced by the geometry of the light source, distance from the object, diffuser use, and optical design. Non-uniform illumination can lead to inconsistent image intensity, making thresholding and feature detection less reliable.

In high-speed systems, lighting is often strobed in synchronisation with the camera exposure to deliver high-intensity illumination over very short durations. This effectively freezes motion and reduces blur while maintaining sufficient brightness for image acquisition.

Reflective surfaces can produce specular highlights and glare, while transparent materials can refract or transmit light unpredictably. These challenges are typically addressed through careful selection of lighting geometry, polarisation, and wavelength to control how light interacts with the material.

In line scan systems, illumination must be highly uniform across the entire scan width and stable over time, as any variation will appear as artefacts in the reconstructed image. Area scan systems are generally less demanding in this regard but still require consistent lighting to ensure repeatable results.

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