Author: Donal Waide

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Vision AI is Transforming Automated Optical Inspection

WOBURN, MA, AUGUST 13, 2025 — In the relentless pursuit for near-zero defects per million (DPM), many manufacturers are turning to Industrial Vision AI for fully automating their inspection processes. Unlike traditional machine vision that relies on rigid, rule-based systems, Vision AI has the agility to learn, adapt and handle day-to-day variability. Using high-resolution imaging technologies, AI algorithms, and real-time processing, Vision AI provides precise, reliable defect detection for meeting rigorous global standards.

One sector aggressively deploying Vision AI is semiconductor fabrication. Manufacturing semiconductors involves multiple steps like deposition, etching, doping, and lithography. During each step, Vision AI is used to identify imperfections that could lead to downstream issues. Along with pinpointing scratches, pattern errors, or particles on wafers, Vision AI inspects etched features at the nanometer scale, verifies uniformity in material deposition, and confirms perfect metallization. For chips requiring soldering or bonding, Vision AI precisely monitors alignment in die bonding, wire bonding, and solder joints. Because of this, Vision AI has proven to improve yield and minimize costly waste.

OPTICAL INSPECTION

For more than a decade, Advantech has driven innovation in Vision AI. Its advanced systems are supercharged by AI Edge servers featuring Intel Xeon scalable processors and leveraging multiple NVIDIA GPU cards to accelerate inspection without compromising performance.

In 2023, we became part of the Advantech family. Our CoaXPress (CXP) and Camera Link interface frame grabbers are now being deployed in Advantech Vision AI, taking these industry-leading systems to the next level in image acquisition. BitFlow frame grabbers are making it possible for Advantech Vision AI to capture and analyze ultra high-resolution images without experiencing latency or frame loss, even in multi-camera setups. Our diverse range of frame grabbers also enables the configuration of modular and scalable Advantech Vision AI systems customized to a manufacturer’s unique processes.

WORKING EXAMPLE

As an example, let’s explore an Advantech Vision AI solution integrated into an optical inspection machine in a semiconductor fabrication plant. Components include:  

  • AI AOI Edge Inference system: Advantech HPC-6240 2U 20” Short-Depth Edge Accelerator Server and ASMB-622V3 5th/4th Generation Intel™ Xeon™ Scalable Proprietary Board supporting 8 expansion slots. 
  • Frame Grabber Card: Axion 4xB Camera Link half-size x4 PCI Express Gen 2.0 frame grabber connected to multiple high-resolution Camera Link cameras 
  • GPU Card: NVIDIA RTX 6000 Ada high-end professional graphics cards handle complex AI computations in visual inspections. 
  • Cameras: Axion-CL frame grabbers support as many as four Camera Link cameras in base, medium, full or 80-bit formats. CL cameras can be synchronized or completely independent, operating at speeds up to 85 MHz.

Faster throughput is possible by substituting the Camera Link interface components for a BitFlow Aon™, Cyton™ or Claxon™ CoaXPress (CXP) frame grabber capable of accelerating transmission speeds to 12.5 Gb/s per link, depending on the model. BitFlow CXP frame grabbers work seamlessly with the Advantech AIR-030 AI Inference System Box based on the NVIDIA Jetson AGX Orin, or the Advantech MIC-770 Compact Fanless System, or several other Advantech IPC options. 

Industrial Vision AI is revolutionizing modern manufacturing by providing a powerful tool for enhancing product quality and operational efficiency. Frame grabbers are a lynchpin in Vision AI, especially in real-time applications requiring latency-free, reliable data transfer.

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BitFlow CoaXPress Frame Grabber Aids in SuperKEKB Particle Accelerator Beam Failure Troubleshooting

 The SuperKEKB particle accelerator in Tsukuba, Japan, was constructed to achieve the highest particle collision rates in the world, enabling next-generation investigation of fundamental physics. SuperKEKB is unique in its employment of a nano-beam scheme that squeezes beams to nanometre-scale sizes at the interaction point, along with the use of a large crossing angle between the colliding beams to enhance electron–positron collision efficiency.

In its quest to reach the world’s highest collision rates, SuperKEKB has repeatedly suffered from Sudden Beam Loss (SBL) events. An SBL event occurs when vertical beam current is reduced by ten percent or more, leading to the process being aborted within a few turns lasting only 20 to 30 milliseconds. It is unknown what specifically invokes an SBL event. According to one theory, beam orbit oscillation causes beam sizes to significantly increase a few turns before an SBL occurrence. Yet it was also observed size escalation started earlier than beam oscillation. Increases have been measured to be up to ten times larger than the usual beam size.

SBL is the biggest obstacle to the longterm stability of SuperKEKB beam operation. It also has the potential to seriously harm accelerator components within the electrons or positrons rings, which are situated side-by-side within a tunnel. Determining the source behind SBL incidents and putting suppressive measures in place were crucial.

IDENTIFYING THE ORIGIN OF SBL

To help uncover the root cause of SBL and ensure redundancy, the SuperKEKB team developed two turn-by-turn beam size monitors operating at different wavelengths; one, an X-ray system for beam size diagnostics, and the other, a visible light monitor focusing on beam orbit variation and size increases.

The 99.4 kHz revolution frequency of the particle accelerator made it necessary to use imaging components compliant with the CoaXPress 2.0 (CXP-12) high-speed standard. In both the X-ray and visible light systems, data transfer rates up to 50 gigabits per second were achieved by aggregating four links between a Mikrotron EoSens 1.1 CXP2 CMOS camera and a BitFlow Claxon CXP4 PCIe quad link frame grabber. During data acquisition, the Mikrotron’s camera shutter was operated in precise synchronization with SuperKEKB’s 99.4 kHz revolution frequency. Captured image data was continuously stored in the BitFlow frame grabber’s 2GB ring buffer. It was only when a beam aborted did the data in the ring buffer move to the disk server for offline analysis.

The Claxon CXP4 is also capable of handling 4 x 1-link cameras, 2 x 2-link cameras or any combination of these.  Each link supports data acquisition of up to 12.5 Gb/s. The highly deterministic, low latency frame grabber will also provide a low speed uplink on all links, accurate camera synchronization, and 13W of Safe Power to all cameras per link.

By reducing the size of the camera’s Region-of-Interest (ROI), the X-ray monitoring system captured 99,400 frames per second, while the visible light system used an ROI twice the size of the X-ray, operating at a speed of 49,700 frames per second. The beam profile was measured with one shot every two turns instead of every turn.

DIFFERENTIATING BEAM PATTERNS

The frame grabber’s CXP-12 transmission speeds empowered SuperKEKB physicists to accurately differentiate between the various beam patterns developing before SBL events occurred.

Combining observations from both the X-ray and visible light monitoring systems, a possible SBL event scenario evolved. Physicists theorized changes in the beam orbit may lead to a sudden increase in vacuum pressure in the damping section of the SuperKEKB with irradiation being the possible source. In this theory, when the beam hits a vacuum component, such as a beam collimator, the result is a sudden loss in beam current and an SBL event. However, this has not been fully clarified. To explore other possibilities, SuperKEKB is developing more advanced X-ray beam-size monitors that combines a silicon-strip sensor with a powerful ADC.

Visible light beam size monitor showing four cables connected to a Mikrotron CXP-12 camera running into a BitFlow Claxon CXP4 PCIe quad frame grabber to achieve 50GB/sec data transfer rates (Image courtesy of SuperKEKB)

Visible light beam size monitor showing four cables connected to a Mikrotron CXP-12 camera running into a BitFlow Claxon CXP4 PCIe quad frame grabber to achieve 50GB/sec data transfer rates (Image courtesy of SuperKEKB

Claxon CXP4

Claxon CXP4 frame grabber

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BitFlow Fiber-over-CoaXPress Frame Grabber Integrated with NVIDIA TensorRT in Real-time Human Pose Estimation

WOBURN, MA, JANUARY 8, 2025 — In collaboration with its parent company, Advantech, BitFlow announced today that it has successfully integrated its Claxon Fiber-over-CoaXPress (CoF) frame grabber with an Advantech AI Inference edge computer and Optronis Cyclone Fiber 5M camera in developing a real-time human pose estimation project accelerated by NVIDIA TensorRT deep learning.

One of the most advanced of its kind, the pose estimation system can provide low latency analysis of athletic movement, gaming, physical therapy, AR/VR, fall detection, and online coaching. Traditional approaches to pose estimation required multiple cameras and special suits with markers, rendering it impractical for most applications. AI-driven computer vision has elevated this field where a single camera can now capture professional-grade, real-time pose estimation. 

With a processing time of less than 2 milliseconds, the system is capable of acquiring 2560 x 1916 resolution images at 600 frames-per-second. Once output to the BitFlow Claxon CoF frame grabber, the Claxon’s Direct Memory Access transmits images directly into the Advantech computer’s GPU memory, reducing bottlenecks and freeing up the CPU to apply an NVIDIA pre-trained algorithm that searches each frame for people. If the algorithm locates a person, it calculates a crude skeleton location and overlays the displayed image with a “stick figure” representing the person’s bone structure.

The Advantech MIC-733-AO AI edge computer is embedded with an NVIDIA Jetson AGX Orin that natively supports the NVIDIA TensorRT ecosystem of APIs for deep learning inference. An optional PCIe x8 iModule is available for the MIC-733-AO to accommodate BitFlow CoaXPress and Camera Link frame grabbers. 

High throughput demands of the system required the use of the BitFlow Claxon CoF model. Designed to extend the benefits of CoaXPress over fiber optic cables, the Claxon Cof is a quad CXP-12 PCIe Gen 3 frame grabber that supports all QFSP+ compatible fiber cable assemblies. In addition to high speeds, fiber cables are immune to EMI and is capable of running lengths well over a kilometer, further than Ethernet’s 100 meter limitations.

Human pose estimation image
Real-time human pose system incorporating BitFlow CoF frame grabber, Advantech AI edge computer, and Optronis fiber camera, accelerated by NVIDIA TensorRT deep learning

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BitFlow Announces Integration of NVIDIA Jetson AGX Orin Module with its Cyton and Claxon CoaXPress Frame Grabbers

Orin with Claxon FXP4

WOBURN, MA, APRIL 9, 2024 — BitFlow announced today that it has successfully integrated the unprecedented computing power of the NVIDIA® Jetson AGX Orin module, which can perform 275 trillion operations per second (TOPS), with the lightning-fast data rates of its CoaXPress (CXP) frame grabbers.

When combined with the NVIDIA AGX Orin Developer Kit, this cost-effective platform empowers engineers to prototype complex machine vision and autonomous inspection applications, leveraging AI accelerated image processing while simultaneously supporting up to four CoaXPress (CXP) cameras and multiple concurrent AI application pipelines. Groundbreaking new applications are more easily developed that augment rule-based machine vision with image-based analysis, making it possible to move beyond “pass/fail” to tasks like image classification, image segmentation, and object detection.

Once proof-of-concept is established, a production model can move forward utilizing an Advantech AIR-030 AI Inference System Box featuring PCI Express x16 and based on the NVIDIA Jetson AGX Orin. As a result of this innovation, Time to Market and associated development costs are significantly reduced.

50GB DATA TRANSFER
BitFlow CXP frame grabbers connect directly to the Jetson AGX Orin via a built-in x16 PCIe slot. Image data may then be transferred at speeds up to 50GB per second from CXP cameras to the NVIDIA Ampere GPU architecture — much faster than what NVIDIA Jetson users are typically limited to using USB3 or GigE Vision cameras. BitFlow CXP frame grabbers DMA directly into the embedded GPU memory for image capture, pre-processing, and machine learning inference, shifting the load from the host computer to avoid CPU overhead.

Besides faster transfer speeds, the CoaXPress interface allows a single cable to carry all data, control, triggering, and up to 13W of power to connected cameras at lengths as far as 100 meters. CoaXPress eliminates the need for multiple cables and a local power supply, therefore giving the system integrator far more flexibility for their prototype designs.

Seamless integration between the NVIDIA Jetson AGX Orin and BitFlow frame grabbers is achieved through BitFlow’s Linux AArch64 SDK. With the SDK being universal, not only is BitFlow’s full line of CXP frame grabbers (Cyton and Claxon families) supported, but additionally the BitFlow Axion Camera Link family is an option for customers.

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BitFlow Enters into Definitive Agreement to be acquired by Advantech

WOBURN, MA, OCTOBER 2, 2023 — BitFlow, Inc., an innovator in frame grabber technology for the machine vision industry, today announced that it has entered into a definitive agreement to be acquired by Advantech in an all-cash transaction representing a 100% equity stake in the company. The transaction was unanimously approved by BitFlow’s Board of Directors and is expected to close during the fourth quarter of 2023.

Advantech is a global leader in embedded, industrial, Internet of Things (IoT), and automation solution platforms headquartered in Taipei City, Taipei, Taiwan, with more than 80 office locations worldwide. Advantech has been a pioneer in integrating Artificial Intelligence (AI) into machine vision systems that transform traditional inspection processes into self-learning Smart Factory applications to improve profitability, drive innovation, and optimize operational efficiency. AI-powered imaging systems go beyond high-quality automated inspection to opportunities for generating information to determine root cause failures, independently measure key performance measures, predict maintenance requirements that reduce costly downtime, and increase the visibility of supply chains, among numerous other value-adding services.

Avner Butnaru, CEO of BitFlow, commented on the acquisition. “The choice to cooperate with Advantech was based on several key factors, including Advantech’s well-known global brand presence in machine vision applications in North America, as well as its global industrial hardware supply capabilities and complete after-sale support and services. Advantech’s manufacturing capability is also crucial to BitFlow. In addition, because of similar corporate cultures, the impact on customers brought about by the integration of Advantech and BitFlow will be greatly reduced. BitFlow believes that by combining its advanced imaging technology and Advantech’s R&D, sales and manufacturing capabilities, BitFlow products will play a much greater role in the AI vision market.”

Upon completion of the transaction, research and development teams for BitFlow and Advantech’s North American business development team will work together to launch innovative new 2D and 3D network devices for the industrial imaging market and fast-emerging AI vision sectors. For instance, BitFlow CoaXPress over Fiber (CoF) frame grabbers will make it possible to link Advantech AI cameras and compute devices using low-cost Fiber cables and connectors for transmission speeds that may soon approach 100 Gbps — two times the current CXP standard — to meet the high bandwidth requirements for AI processing.

As one of the founding technologies in factory automation dating back to the 1970s, machine vision is today at the forefront of the Industrial Internet of Things (IIoT) and AI. Machine vision’s capabilities are being drastically expanded by increasingly powerful computing, embedded and IIoT devices at the network edge, and a growing universe of deep learning AI models. This can permit an imaging system to detect incredibly minute defects, such as microscopic anomalies in the bond wires on a circuit board, resulting in enhanced product quality, a significant reduction in waste, and increased production throughput for companies both large and small.

Magic Pao, Associate Vice President of Industrial Cloud & Video Group said, “The application of advanced computer vision has been highly integrated with AI solutions. Over the last three years, in particular, strong growth in industrial AI has become much more evident. However, in the past, Advantech mainly focused on applications for traditional machine vision equipment, providing industrial-grade cameras and frame grabber cards to meet the basic needs of production inspection. But, as the industry moves towards high-end machine vision applications, such as for advanced semiconductor manufacturing and medical imaging, Advantech will need to supplement high-end image acquisition products to fulfill the demands for high-precision advanced vision inspection.”

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BitFlow Inks New European Distribution Deal 

WOBURN, MA, AUGUST 25, 2022 — BitFlow, Inc. today announced expansion in its international distributor network by signing MaVis Imaging GmbH to represent its portfolio of frame grabbers in Germany, France, Italy, Spain and Portugal through MaVis’ integrated supply chain and customer-centric sales force. 

Headquartered in Taufkirchen, Germany, MaVis Imaging is staffed by a highly regarded team of sales and engineering professionals who will support BitFlow customers to ensure the best image acquisition solution for their application. The collaboration begins immediately with a first order placed this week for BitFlow CoaXPress and CameraLink frame grabbers. 

“We continue to seek outstanding distributor partners who will add value to our frame grabbers by providing outstanding customer service and technical knowledge,” said Donal Waide, Director of Sales for BitFlow, Inc. “MaVis has proven itself to be a successful distributor for many of the industry’s biggest brands, and we are thrilled to have them aboard to represent BitFlow. Our newly formed partnership enables us to expand our presence in targeted markets throughout Europe that are poised for growth opportunities in 2022 and beyond.”

MaVis Imaging GmbH is a company of Framos GmbH, focusing on providing machine vision components and cutting-edge solutions for nearly four decades. From cameras and lighting, to lenses and software, it represents a powerful portfolio of well-known brands such as Effilux, Kowa, Zeiss, Huaray, Sony, and of course, Framos. 

“BitFlow frame grabbers are an ideal compliment to our growing portfolio, especially in light of industry trends towards faster, higher resolution sensors that require the high-speed CoaXPress interface,” said Lorenzo Cassano, CEO of MaVis Imaging. “BitFlow has been setting the global standard for CoaXPress frame grabbers since CXP’s inception with a track record of innovation and success. In addition, BitFlow CameraLink frame grabbers will play a vital role in serving our customers who are seeking a cost-effective acquisition solution for more traditional imaging needs.”

European customers can contact MaVis Imaging at +39 039 888 0585, or visit www.mavis-imaging.com. 

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BitFlow Frame Grabbers Enable Researchers to Leverage CoaXPress into Experimental 3D Profilometry Imaging Technique

Profilometry is an imaging technique used to extract topographical data from a surface in order to obtain surface morphology, step heights and surface roughness. Dynamic 3D surface imaging by phase-shifting fringe projection profilometry (PSFPP) has been widely implemented in diverse applications, including industrial manufacturing, archaeological inspection, entertainment, and biomedicine. PSFPP works by first projecting sets of phase-shifting sinusoidal fringe patterns onto 3D objects and then analyzing deformed structure images reflected from the objects to retrieve 3D surface information.

Existing PSFPP techniques have fallen short in simultaneously providing the robustness in solving spatially isolated 3D objects, the tolerance of large variation in surface reflectance, and the flexibility of tunable working distances with meter-square-level fields of view at video rate. To overcome these limitations, researchers at the INRS Énergie Matériaux Télécommunications Research Centre in Quebec, Canada developed a technique they termed Multi-Scale Band-Limited Illumination Profilometry or MS-BLIP. Supported by the synergy of dual-level intensity projection, multi-frequency fringe projection, and an iterative method for distortion compensation, MS-BLIP can accurately discern spatially separated 3D objects with highly varying reflectance.

The MS-BLIP system begins with a pulsed laser used as the light source. After expansion and collimation, the beam is directed to a 0.45” DMD (Digital Micromirror Device) at an incident angle of ∼24° to its surface normal. Binary fringe masks, generated by an error diffusion algorithm from their corresponding grayscale patterns, are loaded onto the DMD and displayed at up to 1 kHz. A band-limited 4f imaging system that consists of two lenses and one pinhole converts these binary patterns to grayscale fringes at the intermediate image plane. The smallest period in the used sinusoidal fringe patterns is 388.8 µm, which demands a 150-µm-diameter pinhole to pass the spatial frequency components of these patterns while filtering all noise induced by the digital half-toning. A dove prism rotates the generated fringe patterns to match the aspect ratio of the targeted scene. Then, a camera lens (AF-P DX NIKKOR 10-20mm f/4.5-5.6G VR, Nikon) projects these fringe patterns onto 3D objects. The deformed structure images are captured by an Optronis CP70-1HS-M-1900 CoaXPress camera with an Azure lens. Synchronized by the DMD’s trigger signal, the acquired images are transferred to a computer via a cable to a BitFlow Cyton-CXP CoaXPress frame grabber built on a half-size x8 PCI Gen 3.0 express board compliant with the CXP 1.1 standard.

CoaXPress (CXP) is an asymmetric high-speed point-to-point serial communication standard for the transmission of video and still images, scalable over single or multiple coaxial cables. It has a high speed downlink of up to 12.5 Gbps per cable for video, images and data, plus a lower speed uplink up to 42 Mbps for communications and control. Power is also available over the cable (“Power-over-Coax”) and cable lengths of greater than 100m may be achieved.

“Applications for CoaXPress are evolving with new use cases being found in precise medical research and 3D inspection where Camera Link or GigE Vision previously were the go-to standard,” said Donal Waide, Director of Sales for BitFlow, Inc. “Speed combined with stability, plus a growing choice of compatible cameras, have sparked a great deal of interest for CoaXPress in laboratory settings.”

To demonstrate MS-BLIP’s potential in industrial inspection, researchers imaged the rotational movement of a bamboo vase with extending branches rotating at 0.6 rad/s. MS-BLIP was operated at a working distance of 2 meters (m), with an FOV of 1.5 m × 1.0 m, and at a 3D imaging speed of 20.8 frames-per-second (fps). Under these working conditions, the depth resolution was quantified to be 3.7 mm, and the lateral resolution was measured to be 1.7 mm. Close-up views of the vase presented detailed structural information on its surface with depth-encoded color changes of the branches reflecting the rotation movement of the object.

Along with testing with the rotational movements of a craft vase, MS-BLIP also proved successful in the dynamic 3D visualization of translational movements of an engineered box, and full human body movements at a measurement volume 3X greater than existing BLIP systems. Future work will be carried out to improve MS-BLIP’s imaging speed by adopting multiple cameras, a faster DMD, and a more powerful light source. Besides technical improvement, the researchers will continue to explore new applications including automated industrial inspection human-computer interaction.

High-speed dual-view band-limited illumination profilometry using temporally interlaced acquisition C Jiang, P Kilcullen, Y Lai, T Ozaki, J Liang Photonics Research 8 (11), 1808-1817, May 2022

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Researchers Develop Optical Tomography System with BitFlow Frame Grabber to Better Diagnosis Eye Diseases

WOBURN, MA, MARCH 11, 2022 — High resolution 3D imaging of biological tissue is used extensively in the diagnosis of eye diseases, typically by applying a technique known as Optical Coherence Tomography (OCT). OCT testing has become a standard of care for the assessment and treatment of most retinal conditions. It is comparable to ultrasound, except that OCT employs light rather than sound and thereby achieves clearer, sharper resolution.
In a typical OCT system, an optical signal from a broadband source is divided into sample-arm and reference-arm signals using a beam splitter. Both signals are combined and an interference signal is detected by a detector assembly. Some systems employ a wavelength-tuning optical source and are termed “swept source” OCT (SS-OCT). Meanwhile, a system where a stationary broadband signal is dispersed spatially and detected using a spectrometer is referred as a Fourier Domain OCT (FD-OCT).
Both SS-OCT and FD-OCT techniques suffer from changes in the polarization of the optical signal when the signal is transmitted through materials possessing anisotropic properties, meaning they have a different value when measured from different directions. This results in artifacts that compromise the quality of the image, and therefore, the ability of doctors to diagnose a disease.
Reducing Polarization Artifacts Funded by Max-Planck-Gesellschaft and Massachusetts General Hospital, a team of researchers have developed a polarization insensitive detection unit (PIDU) for a spectrometer-based FD-OCT system that greatly minimized polarization associated artifacts in OCT images. The spectrometer unit employed diffraction grating (set at 1200 lines per mm), an 80mm lens, and a Sensors Unlimited InGaAs line-scan camera with a resolution of 2048 pixels.
Data from the spectrometer was collected at a line-scan speed of 100kHz utilizing a BitFlow Axion-CL Camera Link frame grabber. The Axion-CL supports a single Base CL camera, Power over Camera Link (PoCL), and can acquire up to 24 bits at 85MHz. The frame grabber benefits from a PCIe Gen 2 interface and a DMA optimized for fully loaded computers. Data collected by the Axion-CL was processed on LabVIEW software.
To demonstrate the proof of principle in biological tissue the researchers imaged chicken breast because of its high birefringence. Tests were conducted on the OCT system with and without the PIDU. During the imaging, the tissue was held in hand and maneuvered constantly to mimic real clinical conditions. Images were acquired and recorded for 10 seconds.
For the OCT system without PIDU, it was observed that the bright and dark bands of the sample were constantly fluctuating which can be attributed to the polarization dependent phase changes in the sample light. The OCT system with PIDU, however, showed that the image artifacts were not noticeable, making for images that are more accurate for a doctor to observe. Researchers found that in close examination, it was not only the light from the tissue that changes in intensity but also the light from the inner wall of the capsule which is not in tissue contact. This supports the idea that polarization artifacts come not solely from a tissue sample, but can also arise from the system itself.
The researchers believe their new design will be particularly useful in clinical settings where the sample arm is constantly under motion during probe introduction or when it is subjected to peristaltic motion. Further studies are planned on other biological tissues.
David Odeke Otuya, Gargi Sharma, Guillermo J. Tearney, and Kanwarpal Singh, “All fiber polarization insensitive detection for spectrometer based optical coherence tomography using optical switch,” OSA Continuum 2, 3465-3469 (2019)
Schematic of the FD-OCT system employing polarization insensitive detection scheme is shown. SMF: Single mode fiber, Cr: circulator, BS: beam splitter, PC: polarization controller, Co: collimator, NDF: neutral density filter, M: mirror, MPU: motor power unit, EC: electrical connection, MW: motor wire, PBS: polarizing beam splitter, OS: optical switch, G: grating, L: lens, LSC: line scan camera (Image courtesy of Otuya, Sharma, Tearney, and Singh)
(left) Image of chicken breast tissue acquired with OCT system without PIDU and (right) image of the same tissue acquired with OCT system with PIDU (Image courtesy of Otuya, Sharma, Tearney, and Singh)
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BitFlow BFPython API provides Python Wrapper to Enable Rapid Prototyping

WOBURN, MA, FEBRUARY 23, 2022 — BitFlow, a global leader in frame grabbers for machine vision, life sciences and industrial imaging, has introduced BFPython, an application programming interface that allows engineers with Python expertise to acquire images from BitFlow’s broad range of frame grabbers. Available immediately, these Python bindings wrap the BitFlow SDK’s configuration, acquisition, buffer management and camera control APIs. The download also includes several Python examples that illustrate how bindings can be used.

A free, open source programming language, Python is simple to learn and use, making it one of the most popular languages for developing imaging applications, whether in Linux, Windows or embedded platforms. In machine vision, where prototyping is mission critical to understanding how a proposed imaging solution is progressing, BitFlow BFPython accelerates the building process and reduces final development costs for those experienced with Python code. To further assist in development, BFPython includes several sub-modules that provide convenient interfaces to access features such as CoaXPress camera control (via GenICam), Camera Link camera control (via the CL Serial API), among others. 

Supporting the full line of BitFlow frame grabbers, the BitFlow SDK enables developers to bring high-speed image acquisition into machine vision applications, from cost-efficient simple inspection to ultra high-speed, high-resolution systems. The SDK includes a large number of example applications with full source code for aiding in the understanding the available functions, along with a number of utilities for developing and debugging. The free SDK version is for use with third-party applications such as LabVIEW, VisionPro and HALCON. The paid version is required for users developing their own applications, and offers such high-level advantages as header files, libraries and extensive example programs with detailed source code. 

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BitFlow Frame Grabber Helps Researchers Generate 3D Structural Images of Biological Tissues

WOBURN, MA, JANUARY 24, 2022 — Biology researchers at Indiana University1 have developed an integrated system combining high-resolution optical coherence microscopy (HR-OCM) with dual-channel scanning confocal fluorescence microscopy (DC-SCFM) to enable 3D visual evaluation of cell activities involved in pupil developmental and disease conditions. Still in its experimental stages, this dual-modality 3D system simultaneously co-registers reflectance and fluorescence signals, giving it the ability to accurately track structural and functional changes in live specimens over time. Indiana University researchers hope to use their system to enable new investigations of biological processes in small animal models.
A BitFlow Axion Camera Link frame grabber is a critical component of the hybrid system. It acquires the output signal from a spectrometer equipped with a Teledyne e2v high-speed line-scan camera operating at the rate of 250 kHz. A lateral resolution of 2-μm and axial resolution of 2.4-μm is captured in tissue over a field-of-view of 1.1 mm ×1.1 mm. The analog scanning signals, as well as the trigger signals for the BitFlow frame grabber, are generated synchronously through a four-channel analog output data acquisition card. Simultaneous recording of HR-OCM and DC-SCFM data was performed using custom software developed in LabVIEW 2017.
As data generated by faster, higher-resolution Camera Link cameras continues to grow exponentially, the Axion’s PCIe Gen 2 interface, with its StreamSync™ DMA optimized for modern computers, is needed to optimize their full performance. Features such as easier switching between different tap formats, a powerful acquisition engine, and a more flexible I/O and timing generator are all readily available in a dedicated low cost CL Base orientated frame grabber.
During development, researchers applied different strategies to enable the simultaneous recording of information, as well as to overcome the focal plane mismatch between both imaging modalities. The system’s performances were evaluated in imaging fluorescence microspheres embedded in multi-layer tape and silicone phantom. 
The combined system is synergistic in generating structural and functional information of samples; the DC-SCFM allows for the discrimination between different fluorophores, while the HR-OCM enables the 3D localization of the features inside tissue samples and enabled the depth localization.

1 “Development of high-speed, integrated high-resolution optical coherence microscopy and dual-channel fluorescence microscopy for the simultaneous co-registration of reflectance and fluorescence signals” Reddikumar Maddipatla, PatriceTankam School of Optometry, Indiana University, Bloomington, IN 47405, USA

System diagram