Key Takeaways
- Line-scan technology builds images one row of pixels at a time to inspect moving webs and rotating objects.
- An area-scan camera captures a complete two-dimensional frame in a single exposure.
- Choosing the correct sensor type depends entirely on your conveyor speed and the shape of the object you’re inspecting.
The Pitfalls of Choosing the Wrong Camera
Choosing the wrong image acquisition method in machine vision is a bit like choosing to drive a school bus for your daily commute. You’ll eventually get where you’re going, but it will take longer, cost more, and cause frustration throughout the process.
Line-scan and area-scan cameras serve the same general purpose, capturing images to automate visual tasks, but their processes and methods are completely different.
What Is a Line Scan Camera and what are its primary uses?
A line scan camera captures a single row of pixels. As an object moves past the sensor, the camera triggers repeatedly to build an image one row of pixels at a time, stitching these rows together to form a seamless image. The latest line scan imagers range from 500 to 8,000 pixels per line with speeds reaching up to 67,000 lines per second.
Applications where line scan excels:
- Continuous web materials: Paper, film, foil, textiles, and nonwovens
- Cylindrical surfaces: Cans, pipes, and rollers where the camera effectively "unwraps" the surface
- Large planar objects: Solar panels, glass sheets, metal plates, and PCBs wider than a single area scan field of view
- High-speed production: Lines operating at speeds exceeding 2 meters per second, where area scan would require impractical strobe lighting
A line scan camera captures a single row of pixels and stitches them to form a seamless image.
An area scan camera captures a scene in a single snapshot.
What Is an Area Scan Camera and When Does It Win
An area scan camera captures an image in a single exposure. This makes it the most common and flexible choice for inspecting discrete parts – or individual components, as well as robotic guidance and general machine vision applications.
The sensor contains a rectangular array of pixels. In a single snapshot, the camera records the whole scene. Global shutter sensors expose all pixels simultaneously, freezing motion without distortion. This simplicity explains why area scan remains the default for most machine vision installations.
Area scan camera applications include:
- Defect detection for discrete parts: Each part captured individually without motion synchronization
- Robotic bin picking: Single-shot imaging for 3D part location and orientation
- Inspections with multiple regions of interest: One image segmented for multiple defect checks without moving the camera
- Low-speed or stop-and-go lines: Simpler integration without encoder requirements
Area Scan vs. Line Scan: Comparing Features and Applications
Line-scan cameras deliver 20 to 30 times faster inspection speeds than area scan sensors when measuring continuous objects. However, area-scan cameras offer simpler integration with discrete parts and can achieve very high frame rates when inspecting smaller fields of view.
| Area Scan Camera | Line Scan Camera | |
|---|---|---|
| Capture method | Single exposure of a rectangular sensor array | Sequential capture of a single pixel row |
| Image construction | Image in one snapshot | Image stitched from successive rows |
| Maximum practical resolution | 20 to 65 megapixels per frame | 4,096 to 16,384+ pixels per line (infinite length) |
| Average speed | 30 to 500 frames per second (full frame) | 20,000 to 67,000 lines per second |
| Motion requirement | Static or moderate-speed objects | Continuous relative motion (camera or object) |
| Synchronization | Trigger input (external or internal) | Encoder feedback for speed matching |
| Integration complexity | Lower – standard lenses, lighting, mounting | Higher – requires precise motion control and linear lighting |
| Best application type | Discrete parts, presence/absence, assembly inspection, bin picking, multiple regions of interest | Web inspection, cylindrical surfaces, high-speed continuous lines |
Four Critical Mistakes Engineers Make
Motion blur, encoder mismatch, and lighting errors are the three most common and costly mistakes when specifying line- or area-scan cameras. Each mistake is predictable and preventable with proper application analysis.
| Why It Happens | Prevention | |
|---|---|---|
| Motion blur on area scan | Assuming a fast shutter can freeze a web moving faster than 2 meters per second | Use a line-scan system for speeds exceeding 2 m/s |
| Encoder mismatch on line scan | Improper calibration between encoder pulses and camera line rate causes image stretching or compression | Validate encoder resolution and pulse timing with test patterns before production |
| Linear lighting for area scan, ring lights for line scan | Using lighting geometry designed for one camera type on the other | Use uniform line lights for line scan; ring lights or dome lights for area-scan |
| Processing overload | Underestimating data rates from high-resolution line scan systems | Calculate bandwidth requirements early; specify appropriate interface (GigE Vision, CoaXPress, Camera Link HS) |
Line-scan systems require precise synchronization between the camera line rate and conveyor speed, typically via an encoder. If speed changes without matching line rate, the image compresses or stretches, distorting measurements.
Expert Insight: Jon Dizer, Senior Account Sales Engineer
Q: What’s a common aspect of setting up a line scan system people overlook?
A: “Part orientation, for sure. If you can’t get a part in the right position by the time it reaches a camera, you’ll have more problems down the line. Most manufacturers don't have systems in place to rotate parts without slowing down their line speed or reducing throughput. These systems exist, but they are often tricky to fit into existing lines.”
How AI Changes the Camera Selection Equation
AI makes each camera type more capable within its proper application domain by handling organic variations in part appearance, lighting, and defect presentation.
Traditional rule-based vision systems require explicit programming for every possible defect variation. AI tools, including Edge AI and Advanced AI, find defects by learning from example images. This matters for camera selection because an AI-powered camera can tolerate more variation in part positioning and appearance than a traditional system.
Expert Insight: Jon Dizer, Senior Account Sales Engineer
Q: What should someone consider before implementing an AI system, how is that technology going to affect long-term operations?
A: “While AI tools enhance the capabilities of machine vision, there’s no substituting image acquisition. Even small changes to working distance, lighting, or background color can require a full reprogram if the images are drastically different. We’re also getting more questions about how to validate these systems, how to adjust their calibration procedures without affecting an AI model or if tooling or conveyor belts change color.”
“As line scan systems become faster, companies will be able to use advanced AI vision tools, which would have previously created a manufacturing bottleneck. We’re already seeing the segment tool in the In-Sight 3900 becomes a much more viable option now that we can run it fast enough to keep up with modern line speeds.”
Expert Insight: Jon Dizer, Senior Account Sales Engineer
Q: Area scan cameras are getting faster at image acquisition, how is that going to change applications for both technologies?
A: "Area scan cameras are getting faster and faster, enabling them to operate at higher line speeds and expanding the number of applications they can solve and blurring the traditional line scan vs. area scan distinction. But line scan systems are still indispensable when it comes to inspections on cylindrical, shiny targets, like batteries, bottles, vials, and labels.”
The Future of Area and Line Scan: Less PCs, More Imaging Methods
Machine vision is becoming more commonplace. Advanced imaging methods, AI, and image sensors will gradually move from the lab to manufacturing environments, broadening the inspection capacity and capability of machine vision.
- Short wavelength infrared (SWIR) sensors can detect light at a much greater range, allowing it to clearly pass through gas, mist and dust. SWIR can also penetrate certain materials, enabling product inspection even after they’re packaged.
- Edge AI processing will become more routine. Early line-scan systems required massive amounts of image data, and PCs to process that data. Modern systems use Edge AI to compute data, and between hardware and software advancements, Edge AI will get more affordable. This trend will broaden the applications Edge AI can solve and gradually absorb PC-based machine vision.
- 3D profiling and high-frame-rate area scan will blur the traditional line vs. area distinction, allowing line scan to handle large components and area scan to handle continuous webs. As area-scan machine vision systems have more advanced imaging sensors, they will be able to process information at higher framerates, effectively emulating line-scan systems.
Manufacturing engineers will need new skills including AI model training for edge deployment, multi-spectral data interpretation, high-bandwidth interface specification (e.g., CoaXPress-over-Fiber), and hybrid integration of line, area, and 3D imaging.
Area Scan and Line Scan: How Do You Choose?
- Continuous high-speed motion? If your line runs faster than approximately 2 meters per second with continuous product flow, line scan is almost always the answer.
- Long or continuous object dimension? If you inspect webs, pipes, rails, or roll-to-roll materials, line scan handles infinite length seamlessly where area scan would require stitching.
- Wide field of view (FoV) with high resolution? Line scan maintains resolution across any width by increasing pixel count per row. Area scan resolution is fixed by sensor size.
- Discrete parts at moderate speed? Area scan offers simpler integration, lower cost, and easier deployment for most discrete part inspection applications.
Expert Insight: Jon Dizer, Senior Account Sales Engineer
“Almost any time you have a really wide FoV, users underestimate the amount of area scan cameras required to get the same resolution as a line scan camera. Of course, there are usually application-specific reasons to use a specific method, but strictly in terms of resolution – the minimum defect size you need to find – the math almost always points to using a line scan for large FOV inspections.”
Determining the best method for image acquisition is an early step in choosing a machine vision system. Whether you’re implementing your first machine vision system or scaling an existing inspection line, a trusted machine vision system supplier can guide you through the process.