Industrial cameras are key components in machine vision systems. Their fundamental function is to convert light signals into organized electrical signals, thereby enabling the acquisition of digital images. They are widely used in industrial production, inspection, measurement, and other fields. Their imaging principle resembles pinhole imaging but is more complex. Light reflected from the subject passes through the industrial lens, where it is refracted and projected onto the camera's photosensitive sensor. This sensor is typically a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) sensor.
1. Working Principle
Image Acquisition: Light reflected or transmitted from the subject is collected through the lens and focused onto the image sensor.
Photoelectric Conversion: The image sensor (commonly CCD or CMOS) converts light signals into electrical signals. Taking a CMOS sensor as an example, each pixel contains a photodiode that generates charge proportional to light intensity when illuminated, which is then converted into a voltage signal.
Signal Processing: The amplified electrical signals pass through an analog-to-digital converter (ADC) to convert analog signals into digital signals. These digital signals are processed to form digital image data, transmitted to computers or other devices for subsequent analysis.
2. Key Features of Industrial Cameras
High Reliability: Industrial cameras are designed for prolonged continuous operation, ensuring stable performance in harsh environments such as high temperatures, high humidity, and vibration.
High Performance: Delivers high resolution, high frame rates, wide dynamic range, and high sensitivity to meet demands for precision inspection and high-speed capture.
Modular Design: Typically employs a modular architecture for seamless integration into diverse industrial equipment and systems.
Versatile Interfaces: Supports multiple interface types (e.g., GigE, USB 3.0, Camera Link, CoaXPress) to accommodate varying bandwidth and distance requirements.
Flexible Configuration: Supports multiple trigger modes, exposure control, and image processing functions to adapt to diverse application scenarios.
3. Classification Methods
By Image Sensor Type:
CCD Cameras: Offer high image quality and low noise, excelling in low-light conditions, but feature higher costs and power consumption. CMOS cameras are cost-effective, low-power, and feature fast data readout, though image quality is slightly inferior.
By Output Color: Classified as color cameras and monochrome (black-and-white) cameras. Color cameras capture rich color information of objects, suitable for applications requiring color accuracy, such as food appearance inspection and printed material color verification; Monochrome cameras exhibit greater light sensitivity and excel at detecting grayscale variations and texture details in objects. They are commonly used in scenarios requiring high precision, such as dimensional measurement and defect detection.
By scanning method:
Area scan cameras capture a complete frame of an image at once, suitable for detecting static objects or those moving at slow speeds. Line-scan cameras capture one line of an image at a time, constructing the complete image through relative motion between the object and the camera. They are commonly used for detecting high-speed moving objects and high-precision one-dimensional measurements, such as in-line inspection of printed materials and surface inspection of metal sheets.
By output signal type: analog cameras and digital cameras.
By response frequency range: visible light (standard) cameras, infrared cameras, ultraviolet cameras, etc.
4. Key Parameter Calculations
(1) Resolution
Definition: The number of pixels captured per image frame, determined by the resolution of the camera's image sensor. This represents the quantity of pixels arranged on the sensor's target plane.
Impact: During image capture, camera resolution significantly affects image quality. When imaging the same field of view (scene range), higher resolution yields more pronounced detail representation.
Representation: For area-scan cameras, resolution is typically expressed as two numbers: horizontal (H) and vertical (V) resolution, e.g., 1920(H) x 1080(V). The first number indicates the number of pixels per row, while the second number indicates the number of rows of pixels. For line-scan cameras, resolution is usually denoted in thousands (K), such as 1K (1024), 2K (2048), 4K (4096), etc.
Total pixels = Horizontal pixels × Vertical pixels
Example: 1920×1080 = 2,073,600 pixels (approximately 2 million pixels)
(2) Pixel Depth
Definition: The number of bits per pixel, typically expressed in bits.
Impact: Pixel depth determines the richness of an image's grayscale. More bits enhance the ability to express image details, resulting in richer and finer grayscale values. However, this also increases data volume, potentially affecting the system's image processing speed.
Common Values: 8-bit is most commonly used. Digital cameras may also feature 10-bit, 12-bit, or 14-bit configurations.
(3) Maximum Frame Rate/Line Rate
Definition: The rate at which a camera captures and transmits images.
Representation: Frame rate typically applies to area-scan industrial cameras, measured in fps (Frames Per Second), e.g., 181fps indicates the camera can capture up to 181 frames per second. Line rate applies to line-scan industrial cameras, measured in kHz, e.g., 80kHz indicates the camera can capture up to 80,000 lines of image data per second.
Impact: Higher frame rates/line frequencies enable cameras to capture more images per unit time, making them suitable for scenarios requiring rapid motion capture.
Calculation Method: Frame Rate = 3 × Target Speed / Horizontal Field of View; Line Frequency = Motion Speed / Actual Accuracy = Motion Speed × Resolution / Field of View.
Determine the required frame rate based on the object's motion speed in the application scenario. Assuming object velocity V (unit: mm/s) and camera exposure time T (unit: s), where the object's displacement during exposure must not exceed one pixel size P (unit: mm), the frame rate F can be calculated as: F = 1/T, where T ≤ P/V.
(4) Exposure Method and Shutter Speed
Exposure Mode: For line-scan cameras, progressive scan exposure is typical. Area-scan cameras commonly employ frame exposure, field exposure, or rolling shutter exposure.
Shutter Speed: Typically achievable down to 10 microseconds, with high-speed cameras capable of even faster speeds. Faster shutter speeds enhance the camera's ability to capture images, making them suitable for scenarios with rapidly changing light conditions or moving subjects.
(5) Pixel Size (Pixel Size)
Definition: A pixel is the smallest unit composing a digital image. Pixel size and pixel count (resolution) jointly determine the camera's target area size.
Common Values: Industrial camera pixel sizes typically range from 3μm to 14μm.
Impact: Larger pixels capture more photons, generating greater charge under identical lighting and exposure conditions, potentially yielding higher image quality. However, smaller pixel sizes increase manufacturing complexity.
Calculation: Depends on resolution and camera sensor dimensions. For example, given a sensor size of Sa × Sb (horizontal × vertical dimensions in mm) and a camera resolution of Na × Nb, the pixel size P (assuming square pixels) is: P = Sa × 1000 / Na = Sb × 1000 / Nb.
(6) Spectral Range
Definition: Refers to the sensitivity characteristics of the pixel sensor to different wavelengths of light.
Common Range: Typically responds between 350nm and 1000nm. Some cameras incorporate a filter in front of the sensor to block infrared light. If infrared sensitivity is required for the system, this filter can be removed.
(7) Interface Type
Common Types: Camera Link, Ethernet, 1394, USB output, etc. The latest interface is CoaXPress.
Impact: The interface type determines how data is transferred between the camera and image processing systems or other devices. Selecting the appropriate interface ensures stable and fast data transmission.
(8) Sensor Size
Definition: The physical dimensions of the camera sensor, typically expressed in inches (e.g., 1/2.3") or millimeters (e.g., 12.8mm × 9.6mm).
Calculation Method:
Sensor size is usually provided by the manufacturer but can be estimated from pixel dimensions and resolution:
Sensor width = Horizontal pixel count × Pixel size
Sensor Height = Vertical Pixel Count × Pixel Size
(9) Other Parameters
Dynamic Range: Describes the number of gray levels each pixel can distinguish. Wide dynamic range enables clear capture of details in both bright and dark areas of a scene.
Noise: Unwanted signals captured during imaging that are unrelated to the actual imaging target. According to the EMVA1288 standard of the European Machine Vision Association (EMVA), camera noise is broadly categorized into two types: shot noise derived from the effective signal and inherent noise intrinsic to the camera itself, independent of the signal.
5. Application Fields and Advantages
Industrial cameras are widely used in quality control on automated production lines, machine vision systems, medical imaging, logistics and warehousing, security surveillance, traffic monitoring, as well as military and aviation applications. Their advantages include:
High Performance and Stability: Industrial cameras offer high image stability, robust transmission capabilities, and strong interference resistance, enabling prolonged stable operation under harsh conditions.
High Precision and Measurement Capabilities: Through high-resolution image capture and precise image analysis algorithms, industrial cameras achieve high-accuracy measurement and positioning.
High-Speed Capture Capabilities: High-frame-rate industrial cameras rapidly capture dynamic images, making them suitable for photographing and monitoring fast-moving objects.
Wide Adaptability: Diverse industrial camera types cater to varied application scenarios and requirements, fulfilling complex imaging and analysis tasks.
6. Renowned Brands
Leading global industrial camera brands include Cognex, Keyence, Canada's Teledyne DALSA, FLIR, Lumennera, Japan's AVALDATA, South Korea's VIEWORKS, Daheng Imaging, and Hikvision. These brands are highly regarded for their exceptional performance and broad application domains.
In summary, industrial cameras serve as critical components within machine vision systems, playing a vital role in industrial automation and intelligent manufacturing. By selecting appropriate industrial cameras and integrating advanced image analysis algorithms, more efficient, precise, and reliable automated production and quality control can be achieved.