Precision Lighting. Perfect Vision.
LuxMV designs and manufactures professional LED light sources, intelligent strobe controllers, and high-resolution industrial lenses. Empowering global automated inspection with flawless contrast.
Engineered Components
Discover our complete range of standard machine vision hardware, rigorously built to meet industrial reliability requirements.
Machine Vision Light
High-uniformity LED illumination systems, including ring, bar, coaxial, and backlights for perfect contrast.
View CatalogCustom Light
Tailor-made optical housings, multi-wavelength lights, and bespoke form factors for unique visual checks.
View CatalogFiber Optic Light
High-intensity fiber optic illuminators and flexible light guides for microscopic and spot inspection.
View CatalogController
Digital strobe controllers with precise current tuning, external trigger sync, and multi-channel control.
View CatalogLens
High-resolution telecentric and macro lenses featuring low distortion, high depth of field, and crisp details.
View CatalogCamera
Industrial-grade area and line-scan cameras for high-speed, high-accuracy inspection and image capture.
View CatalogAccessories
Optical diffusers, polarizers, brackets, and expansion modules designed for robust industrial setups.
View CatalogPrecision Customization & Support
We deliver more than hardware; we engineer optical systems that resolve imaging challenges in complex automated inspection lines.
15+ Years Customization
Specialized optical and mechanical engineering to create customized light paths, custom housings, and specific wavelengths for non-standard visual inspections.
Free Sample Loan Program
Access our inventory of thousands of demo light sources and lenses. Test on your actual target parts to ensure perfect contrast before finalizing your software code.
Advanced Optical Labs
State-of-the-art testing labs featuring high-stability spectral analyzers, uniformity mapping tools, and 3D simulation to model reflections and lighting angles.
Fast-Track Lead Times
Highly automated assembly lines and deep inventory on raw LEDs and optics guarantee rapid delivery and seamless integration into your machine building schedule.
Case Studies & News
Explore deep technical articles, selection guides, and industry application cases compiled by LuxMV optical engineers.
How do machine vision designers choose the right lens?
Language HOME ABOUT LuxMV PRODUCTS APPLICATIONS SERVICE SUPPORT PRESS CONTACT US Go! News ARTICLE How Do Machine Vision Designers Choose The Right Lens? For machine vision system designers, the cost-performance trade-off when selecting a lens for a specific application becomes more complicated because there are many different types of lenses with different resolutions and different image distortion characteristics available on the market. Fixed-focus lenses remain the mainstay of many machine vision systems due to their low cost; however, there are many other lens options on the market, including zoom, telecentric, 360° optical and liquid lens products, each with its own unique advantages in meeting specific applications. Determine Focal Length Before selecting any particular lens, its focal length must be determined. The choice of focal length depends on the resolution required for the imaging defect, the size of the object being imaged, and the distance of the object from the camera. The focal length in this context refers to the distance between the optical center of the lens and the camera's image sensor. By changing the focal length of the lens, different sizes of field of view (FOV) can be obtained. Choosing the correct focal length of the lens depends on the working distance of the object from the camera/lens system, the required field of view and the size of the image sensor. The focal length of the lens can be determined by the following formula: Focal length = magnification × working distance / (1 + magnification) where magnification = sensor size / FOV. Therefore, for the same working distance, a larger sensor size will produce a larger field of view. When selecting a lens, the resolution of the lens must match the characteristics of the camera's image sensor. To do this, it is important to understand the characteristics of the image sensor used in the camera. The resolution of a camera is determined by the pixel size of the image sensor, which can be calculated in line pairs per mm (lp/mm) as follows: 1000 (lp/mm) / 2 × pixel size (μm) Fixed focus or zoom? Fixed focus lenses are widely used in machine vision systems because they use fewer optical components, have low optical distortion, and are relatively inexpensive. However, in some applications, the field of view may need to change, especially when the system design may change over time, or when the system integrator needs to determine the appropriate focal length for a certain application. In this case, a zoom lens can be selected. Unlike a zoom lens, which maintains the focus position unchanged when the focal length changes, a zoom lens requires refocusing while allowing different fields of view to be imaged. Enlarge Although zoom lenses are not common in machine vision applications, they are often used in applications such as microscopy to provide manual or motor-controlled image magnification. Using such a zoom lens allows the operator to inspect parts at the desired magnification without having to change lenses, or to mount multiple lens types on a lens tray (which allows the magnification to be changed without removing or loading the lens). Using a zoom lens, the inspection system can be automated so that the system can be programmed to view the entire scene at low magnification and zoom in on specific details without having to change lenses or rotate the lens tray. Telecentric Design With traditional lenses, the closer an object is to the camera, the larger the image appears; the farther the object is from the camera, the smaller the image appears. This is a disadvantage in high-precision measurement applications because image processing software will measure the parameters of the part based on the captured image. To overcome this problem, system developers can use telecentric lenses so that they can obtain images of objects of the same size, regardless of the object's position in space. The distance an object can move and still appear the same size after being imaged is called the magnified depth of field. The magnified depth of field is different from the image clarity depth of field, which is the depth of field we usually understand. Compared to traditional lenses, telecentric lenses are usually larger and more expensive because they require more lens elements and the lens needs to be as large as the object being imaged. There are three types of telecentric lenses on the market today - object-space telecentric lenses, image-space telecentric lenses, and bi-telecentric lenses. Although many manufacturers offer all three types of telecentric lenses, image-space telecentric lenses are more commonly used in image projection equipment and are less commonly used in machine vision. For example, in lithography systems, projection lenses are typical image-space telecentric lenses used to image lithography masks onto silicon wafers. The advantage of such image-space telecentric lenses is that they provide uniform light transmission across the field of view. The most commonly used telecentric lenses in machine vision systems are object-side telecentric lenses and bi-telecentric lenses. Object-side telecentric lenses require fewer lens elements than bi-telecentric lenses and are therefore less expensive. Object-side telecentric lenses are telecentric on the object side, while bi-telecentric lenses are telecentric on both the object and image sides, providing constant magnification even when the imager in the camera cannot always be in the exact position in the optical path. Such bi-telecentric lenses are often used with collimated backlight illuminators to ensure high contrast images for accurate image measurement. Reduce camera costs For applications such as beverage, pharmaceutical and cosmetic inspection, parts must be inspected at high speeds as they move along a conveyor. To do this, a system must be built that can image the sides, tops and even inside containers to detect defects. Of course, there are many different ways to accomplish this task. This can be accomplished using multiple cameras to image the top and sides of the object. Here, multiple cameras, mounting brackets, and software calibration routines can be used. Alternatively, the object can be rotated around the field of view of a single line scan camera or area scan camera to capture a 360° image of the object. This approach requires more complex mechanical engineering because the object must be stopped, rotated, and inspected before a pass/fail decision can be made. Electric focus While conventional lenses can be used to image objects at different distances from the camera, if objects of different heights appear in the imaging system, the lens will need to be refocused. While manual focus adjustment can be performed on automated production lines, this requires resetting the camera for different focal lengths. Manual adjustment requires time to adjust, resulting in increased downtime; on the other hand, manual adjustment can be difficult if the camera and lens are mounted in hard-to-reach areas of the equipment. Although currently available lenses can meet the needs of many machine vision applications, more specialized machine vision systems may require custom lenses and coatings. 2025-06-28 10:28:56 << Previous Page Next Page>> ARTICLE Press HOT ARTICLE (LuxMV)AOI Applications Light L LuxMV SWIR Light Applications New Product For Concave-Convex Condenser Lens For Mounting On 4 Generation High Uniformity L x ABOUT US LuxMV (Lighting & Tech Specialist) is a leading organization in developing and manufacturing machine vision lights for the advanced lighting industry. We supply a broad range of solutions in light, lenses and cameras. PRODUCT Machine Vision Light Custom Light Controller Fiber optic light Camera Lens Accessories CONTACT US info@luxmv.com QUICK CONTACT Send Message Copryright 2019 LuxMV -
Read Article
Characteristics of infrared images and detection difficulties
Language HOME ABOUT LuxMV PRODUCTS APPLICATIONS SERVICE SUPPORT PRESS CONTACT US Go! News ARTICLE Characteristics Of Infrared Images And Detection Difficulties Infrared images, as an important imaging method in the field of target detection, have their own unique characteristics and detection difficulties. Infrared images are mainly based on the infrared radiation emitted by objects. This imaging method makes infrared images have broad application prospects in the field of target detection. 1. Characteristics of infrared images (1) Reflecting the thermal distribution of objects: Infrared images can reflect the thermal distribution information of objects, which is very useful for detecting temperature anomalies or thermal failures. For example, in industrial production, infrared images can be used to detect thermal failures of equipment and discover potential safety hazards in a timely manner. (2) Penetrating imaging: The infrared imaging system does not require an external light source and can perform imaging at night and in low light conditions. It has strong penetrating properties and is suitable for target detection and monitoring in severe weather conditions. (3) Low image contrast: Due to the working principle of the infrared imaging system and the limitations of the detector, infrared images often have low contrast, making the target details and contour information unclear. This increases the difficulty of target detection to a certain extent. (4) Noise interference: Infrared images often contain various noise interferences, such as fixed noise, random noise, etc. These noises not only reduce the image quality, but also may cover up the characteristic information of the target, and have a negative impact on the performance of the target detection algorithm. 2. Difficulties in infrared image detection in the field of target detection (1) Target features are not obvious: Infrared images mainly reflect the thermal information of objects rather than visual features such as shape and color. Therefore, in infrared images, targets often lack obvious features such as shape and texture, which makes it difficult to apply traditional feature-based target detection algorithms in infrared images. (2) Background interference: The background in infrared images often contains a large amount of thermal information, which is intertwined with the thermal information of the target, making it difficult to separate the target from the background. Especially in complex environments, such as city streets and forests, the thermal distribution of the background is complex and changeable, which poses a great challenge to target detection. (3) Noise influence: Noise in infrared images not only reduces image quality, but also may mask the characteristic information of the target. In the target detection process, noise may cause false alarms or missed detections, reducing the accuracy of detection. Therefore, how to effectively extract target features and perform accurate detection under noise interference is an important difficulty in infrared image target detection. (4) Uncertain shape: The scale and shape of infrared targets vary significantly in different scenarios. For example, obstacles such as leaves and buildings may block the target, making the target appear incomplete or blurred in the infrared image. This makes the detection problem quite challenging. 2025-07-12 09:38:02 << Previous Page Next Page>> ARTICLE Press HOT ARTICLE (LuxMV)AOI Applications Light L LuxMV SWIR Light Applications New Product For Concave-Convex Condenser Lens For Mounting On 4 Generation High Uniformity L x ABOUT US LuxMV (Lighting & Tech Specialist) is a leading organization in developing and manufacturing machine vision lights for the advanced lighting industry. We supply a broad range of solutions in light, lenses and cameras. PRODUCT Machine Vision Light Custom Light Controller Fiber optic light Camera Lens Accessories CONTACT US info@luxmv.com QUICK CONTACT Send Message Copryright 2019 LuxMV -
Read Article
How autofocus works: How cameras and lenses achieve precise focus
Language HOME ABOUT LuxMV PRODUCTS APPLICATIONS SERVICE SUPPORT PRESS CONTACT US Go! News ARTICLE How Autofocus Works: How Cameras And Lenses Achieve Precise Focus How autofocus works: How cameras and lenses achieve precise focus Whether capturing a fleeting expression, fast-moving wildlife, or cinematic video footage, autofocus systems are designed to keep subjects sharp, responsive, and accurate. But behind this ease is a complex interplay between the camera’s detection system and the lens’ built-in motors. To understand how autofocus works, and why some systems work well in certain scenes while others don't, we have to look at how the camera determines where to focus, and how the lens actually executes that instruction. These two components work in tandem, and the effectiveness of one often depends on the accuracy of the other. Autofocus is not a single system, but a layered architecture of optical, electronic, and mechanical processes that vary from brand to brand and even from lens to lens. Camera-Based Autofocus Systems The first half of the autofocus process occurs inside the camera body. Here, the system "decides" where to focus by analyzing the scene and measuring sharpness through various detection strategies. Contrast Detection Autofocus Contrast detection is the most intuitive and mathematically simplest autofocus method. It is based on a familiar principle: the sharpest image is the one with the highest local contrast, just like when you squint your eyes to focus. In digital cameras that use this method, the sensor evaluates contrast by measuring the difference in brightness between adjacent pixels. As focus changes, contrast gradually increases until it reaches a peak. At this point the camera stops focusing because it has determined that maximum sharpness has been achieved. This process is iterative and non-predictive, and the lens must move past the best focus position and back again to confirm that the sharpest contrast point has been found. While highly accurate in static scenes, contrast detection falls short in speed. Since it doesn't know in advance the direction and distance the lens needs to move, "focus hunting" is common in low-light environments or when photographing low-contrast subjects. This can cause delays in action photography and missed focus moments. However, the accuracy of this method makes it valuable when photographing static subjects, studio work, or video scenes, where accuracy is more important than speed. Phase Detection Autofocus Phase detection autofocus turns focusing into a geometry problem. Unlike contrast detection, which evaluates sharpness after moving the lens, phase detection estimates the direction and amount of movement required before you start moving the lens. This pre-calculation makes phase detection much faster. In SLR systems, phase detection usually involves a separate AF module located within the camera body, which uses mirrors and beam splitters to direct part of the incoming light to a dedicated sensor. In mirrorless systems, phase detection pixels are embedded directly into the image sensor. This allows the camera to capture the image and analyze the focus at the same time. The system works by comparing two versions of an image projected from either side of the lens. When the two projections are in phase, the image is in focus. If they are out of phase, the system can instantly tell whether the lens needs to be moved closer or farther away, and approximately how much. This speed and directionality makes phase detection ideal for capturing fast-moving subjects and for continuous autofocus tracking. However, in SLR architectures, phase detection is prone to calibration errors. Since the AF sensor and image sensor are physically separated, slight misalignments can occur, known as front or back focusing. Mirrorless systems with on-sensor phase detection have largely solved this problem, combining accuracy with speed. Hybrid Autofocus Recognizing the complementary strengths of contrast and phase detection, many manufacturers are now combining the two technologies into hybrid systems. In these systems, phase detection provides a fast, coarse focus estimate, while contrast detection refines the result for precise sharpness. This synergy reduces focus hunting while maintaining precision, and has become the standard approach on most modern mirrorless cameras. Hybrid systems are especially effective in video AF, where smooth transitions and accurate tracking are critical. The fusion of these technologies also delivers better performance in a wider range of shooting scenarios, from high-speed sports to quiet interviews. Dual Pixel Autofocus Dual Pixel CMOS Autofocus (DPAF) is a unique (and proprietary) implementation of phase detection that relies entirely on the image sensor. Because nearly every pixel is involved in both image creation and focus detection, DPAF achieves nearly 100% AF coverage and remarkably smooth subject tracking. The system is particularly valuable in video, where it is prized for its ability to follow complex subject movements without focus hunting or jumping. AI-based autofocus and subject recognition More and more modern autofocus systems are integrated with artificial intelligence. These systems can detect and prioritize specific subjects — faces, eyes, animals, vehicles, etc. — not only based on focus metrics, but also through pattern recognition and predictive learning. These algorithms analyze visual data and make context-aware decisions about which parts of the scene should remain in focus, even if the subject is partially obscured or moves unpredictably. AI AF not only makes tracking more accurate, it’s also more intuitive. It allows photographers to focus on timing and composition, trusting that the camera will take care of the technical precision aspects. Lens-based AF systems While the camera decides where to focus, the lens is responsible for executing that decision. The AF motor within the lens physically moves internal elements to adjust the focal plane. These motors vary widely in performance, noise, and video compatibility. Conclusion Autofocus is no longer just a convenience, but a fundamental aspect of how photographers interact with their subjects. From the fast calculations of phase detection to the deliberate refinement of contrast detection, autofocus technology varies. As camera systems evolve, autofocus continues to be an area of intense innovation. 2025-07-19 09:09:36 << Previous Page Next Page>> ARTICLE Press HOT ARTICLE (LuxMV)AOI Applications Light L LuxMV SWIR Light Applications New Product For Concave-Convex Condenser Lens For Mounting On 4 Generation High Uniformity L x ABOUT US LuxMV (Lighting & Tech Specialist) is a leading organization in developing and manufacturing machine vision lights for the advanced lighting industry. We supply a broad range of solutions in light, lenses and cameras. PRODUCT Machine Vision Light Custom Light Controller Fiber optic light Camera Lens Accessories CONTACT US info@luxmv.com QUICK CONTACT Send Message Copryright 2019 LuxMV -
Read ArticleHave a challenging optical inspection task?
Get in touch with a LuxMV application engineer today. We provide free selection, optical calculations, and sample loans.
Consult an Engineer