In most applications, industries are applying SWIR cameras to quality control and maintenance, as it is capable of finding the defects and problems that are impossible to detect with other imaging technologies. Factors such as enhanced visibility, technological advancements, and versatility in penetration through materials like plastic and fabrics are the growth of the market for this segment. SWIR systems are crucial in food & beverages, semiconductor wafer inspection, and automotive applications, among others. SWIR also has significant potential applications in consumer electronics.

From the previous section, we understood the definition of FOV and its relation with several other lens parameters. Let us now discuss how to choose the right FOV for an embedded vision application.

However, it is extremely important to understand that many factors determine this. There is no ‘one-size fits all’ approach to this. It is recommended that you seek help from an imaging expert like e-con Systems as you pick the right field of view and lens for your application.

Cooled SWIR imagers provide superior sensitivity, higher resolution, and better performance in low light and challenging circumstances, making them ideal for monitoring & inspection and surveillance where temperature differences might occur.

In this article, let’s explore the importance of FOV in embedded vision, the factors that determine FOV, as well as which applications rely on this the most.

Similarly, for the calculation of VFOV and DFOV, instead of width (or horizontal F0V), corresponding height and diagonal dimensions of the object are substituted in the above formula respectively.

After arriving at the overall market size from the estimation process explained in the previous section, the total market was split into several segments and subsegments. The data triangulation procedure was employed, wherever applicable, to complete the overall market engineering process and arrive at the exact statistics for all segments and subsegments. The data was triangulated by studying various factors and trends from the demand and supply sides, and the market size was validated using top-down and bottom-up approaches.

FOV also depends on the distance between the camera and the object. As discussed earlier, if the objects are closer to the camera, the FOV becomes wider. This is because shorter focal lengths require shorter working distances for proper focusing. Thus, the lens to sensor distance has to be designed based on the working distance.

The depth of field is the zone within a photo that appears acceptably sharp and in focus. In every picture, there is a point of focus – the spot where you ...

Automated sports broadcasting systems use cameras with a wide FOV to cover entire fields or courts. Hence, all the movements within the sporting area are captured, which means viewers can experience the game in an immersive way. A wide FOV is also important for capturing aspects such as player movements and strategic plays, which enhances the overall broadcasting quality. Furthermore, wider FOV cameras streamline production by potentially replacing multiple conventional cameras, reducing setup complexity and personnel needs.

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Many modern-day embedded vision systems utilize multiple types of lenses and sensors with different feature sets and varying costs. The design of the camera systems integrated with these components plays a huge role in achieving the required image quality.

However, selecting and evaluating sensors and lenses can be challenging. The right combination can help build a highly optimized embedded vision system that meets all your standards. Of course, when selecting a lens for an embedded camera, numerous factors, such as Field Of View (FOV), must be considered.

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Focal length is the defining property of a lens. Simply put, it is the distance between the lens and the plane of the sensor, and is determined when the lens focuses the object at infinity. It is represented in mm. Focal length depends on the curvature of the lens and its material. The shorter the focal length, the wider the AFOV and vice versa. Please have a look at the below image to understand this better:

Let’s look at Autonomous Mobile Robots (AMR) as a reference. These autonomous systems perform obstacle detection and obstacle avoidance (ODOA) to seamlessly navigate their environment. Many of them require FOVs in excess of 180 degrees. This ultra-wide FOV is achieved by using multi-camera systems.

North America commands a large share of the SWIR market. The expanding SWIR sector and industry demands are driving the adoption of SWIR in the North American market. However, increasing funding for R&D focused on enhancing the analytical capabilities of SWIR facilitates the high growth of SWIR solutions in the Asia Pacific region.

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Having two or more cameras enables a higher resolution, prevents lens distortion, and offers a wider FOV. To achieve high imaging quality in multi-camera systems, a lens having an FOV of around 60-70 degrees is usually chosen.

Please write to us at camerasolutions@e-consystems.com if you need expert help integrating cameras with different FOVs into your applications.

For example, imagine that the camera and the object are fixed at a working distance of 30cm. In this case, the HFOV and VFOV are measured manually using a scale (in mm) as shown below:

Most embedded camera applications require the FOV to be wider enough to cover a large viewing area. For instance, a fish-eye lens is characterized by a wider FOV and larger depth of field (DOF) and is hence suitable for surveillance applications. On the other hand, for a zoom/telescopic application, you might require a normal/narrow FOV.

Field of view (FOV) is the maximum area of a scene that a camera can focus on/capture. It is represented in degrees. There are three ways to measure the field of view of a camera – horizontally, vertically, or diagonally as shown below.

What helps e-con stand out when it comes to this solution is our proprietary 180-degree stitching algorithm that can process images from multiple cameras to create a 180 degree image. To learn more about this solution, please visit the product page.

fov是什么

In the complete market engineering process, top-down and bottom-up approaches and several data triangulation methods have been used to estimate and forecast the overall market segments and subsegments listed in this report. Key players in the market have been identified through secondary research, and their market shares in the respective regions have been determined through primary and secondary research. This entire procedure includes the study of annual and financial reports of the top market players and extensive interviews for key insights (quantitative and qualitative) with industry experts (CEOs, VPs, directors, and marketing executives).

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Also, let us consider a popular embedded vision application like autonomous mobile robots (AMR). These autonomous systems perform obstacle detection and obstacle avoidance (ODOA) to seamlessly navigate their environment. And many of these robots require FOVs in excess of 180 degrees. This ultra-wide FOV is achieved by using multi-camera systems.

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For old sensor/binary sensor configuration format, see below. State-based template binary sensors, buttons, images, numbers, selects and sensors. Template ...

Conversely, if you know the FOV and the working distance, then you can calculate the dimension of the object using the below formula.

Industrial automation systems for functions like quality inspection rely on cameras with accurate FOV settings to scrutinize products on assembly lines. They capture imaging data required for thorough product inspection by detecting defects instantly. Moreover, manufacturers can optimize their inspection processes, reduce errors, and maintain consistent product standards.

Each embedded vision application has different sensor size requirements to get the best output. A small sensor will have a narrow field of view while a large sensor can provide a wide field of view.

Meanwhile, you could check out the article What are the crucial factors to consider while integrating multi-camera solutions? if you are interested in learning more about multi-camera integration.

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A lower signal-to-noise ratio in images makes it hard to understand the fine details and reduces image quality and clarity. The signal-to-noise ratio in a SWIR imager makes a huge difference in seeing and not seeing an object in question. In SWIR, achieving a higher signal-to-noise ratio is important as it impacts the accuracy and output of information captured by the imagers. Improvements in signal-to-noise ratio are crucial for clearer images and more reliable outputs.

Broad perspectives generally equip Autonomous Mobile Robots to navigate complex environments and avoid obstacles. A wide FOV also ensures that robots can detect and analyze their surroundings in real time, boosting their ability to move safely and operate in dynamic environments, such as warehouses, manufacturing floors, and public spaces. A large vertical FOV ensures that obstacles at any height are detected, allowing robots to navigate under hanging obstacles such as shelves or overhead conveyor. For warehouse AMRs, two cameras placed on opposing corners, each providing a 270° FOV, can offer complete situational awareness. This setup enables the AMR to navigate freely in all directions—left, right, forward, and backward—while also turning efficiently without worrying about blind spots or objects coming from behind.

For imaging in this range, SWIR cameras convert the radiation of objects in the SWIR range to a measurable form. The capability of a SWIR camera depends on the type of component used. Lenses and detectors are the two most essential components of a SWIR camera and account for a significant percentage of the total parts of a SWIR camera. Indium gallium arsenide (InGaAs), mercury cadmium telluride (HgCdTe), and indium antimonide (InSb) are a few of the types of SWIR detectors available in the SWIR market.

Smart traffic systems utilize cameras with a wide FOV to seamlessly monitor and manage road traffic. Such cameras capture comprehensive views of large areas for performing real-time traffic flow analysis and incident detection. Covering wide road sections also means they can promptly identify traffic violations, accidents, and congestion. Additionally, the broader view empowers advanced features like vehicle counting, object classification and lane discipline monitoring. This provides crucial real-time data that helps optimize traffic flow and improve overall safety.

Having 2 or more cameras enables a higher resolution, prevents lens distortion, and offers a wider FOV. To achieve high imaging quality in multi-camera systems, a lens having an FOV of around 60-70 degrees is usually chosen. But it is important to note that this is determined by a multitude of factors. There is no ‘one-size fits all’ approach to this. It is recommended to take the help from an imaging expert like e-con Systems as you go about picking the right field of view and lens for your application. Please feel free to write to us at camerasolutions@e-consystems.com if you need a helping hand.

Various secondary sources have been referred to in the secondary research process to identify and collect information important for this study. The secondary sources include annual reports, press releases, and investor presentations of companies; white papers; journals and certified publications; and articles from recognized authors, websites, directories, and databases. Secondary research has been conducted to obtain critical information about the industry’s supply chain, the market’s value chain, the total pool of key players, market segmentation according to the industry trends (to the bottom-most level), regional markets, and key developments from market- and technology-oriented perspectives. The secondary data has been collected and analyzed to determine the overall market size, further validated by primary research.

Companies such as Teledyne FLIR LLC (US), Leonardo DRS (US), Corning Incorporated (US), Allied Vision Technologies GmbH (Germany), and Collins Aerospace (US) are some of the leading players in the global SWIR market.

The Asia Pacific region is projected to register the highest CAGR in the SWIR market. The high growth of the market is attributed to rapid industrialization, primarily in China, Japan, and South Korea. The region is a major base for electronics, automotive, and semiconductor manufacturers.

FOV is one of the most critical parameters considered while integrating a camera into an embedded vision system. Whether it’s an intelligent transportation system, autonomous mobile robot, remote patient monitoring system, or automated sports broadcasting device, FOV plays a major role in ensuring the necessary details of the scene are captured. The FOV of the lens can be set as wide or narrow based on the end application requirements.

e-con Systems has led from the front when it comes to innovation in embedded vision. And one of our key strengths is the platform side expertise especially on the NVIDIA Jetson series. Leveraging this, e-con has designed many multi-camera solutions that offer an FOV of up to 360 degrees.

With the given market data, MarketsandMarkets offers customizations according to the company’s specific needs. The following customization options are available for the report:

Markets and Markets research pvt ltd. (Aug, 2024 ). Shortwave Infrared (SWIR) Market Size, Share & Industry Trends Growth Analysis Report by Camera, Lenses, Spectral Imaging, Area & Line Scan, Active & Passive Thermal Imaging, Pushbroom, Snapshot, Security & Surveillance, Monitoring & Inspection, Technology, Vertical and Region – Global Forecast to 2029 MarketsandMarkets. Retrieved Nov  8, 2024, from https://www.marketsandmarkets.com/Market-Reports/shortwave-ir-market-52975079.html

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The camera's FOV determines how much of the scene can be captured simultaneously. For SWIR cameras, expanding the FOV can be challenging due to limitations in optics, sensor design, and system architectures. A wide FOV is desirable when capturing big areas; however, the resolution is compromised, or system complexity is highly increased.

Major players operating in the SWIR market are Teledyne FLIR LLC (US), Corning Incorporated (US), Collins Aerospace (US), Allied Vision Technologies GmbH (Germany), and Leonardo DRS (US), among others.  (A total of 25 players have been profiled)

Now let us discuss FOV calculation. In many applications, the required distance from an object and the desired field of view (which determine the size of the object seen in the frame) are known quantities. This information can be used to directly determine the required angular field of view (AFOV) as shown below.

fov参数

Short Wave IR (SWIR) is a subset of the infrared band in the electromagnetic spectrum, covering wavelengths ranging from 1 to 3 microns. This wavelength is not visible to human eyes and can often offer a better image than what is achievable with visible light imaging. A number of manufacturers make SWIR imagers that detect various ranges of the electromagnetic spectrum with multiple qualities.

Field of view

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Remote patient monitoring systems rely on cameras with an optimal FOV to provide accurate and complete observations of patients. These cameras ensure that all relevant movements and conditions are captured so that healthcare providers can monitor the health of patients. It leads to timely medical interventions and improved remote patient safety.

Hence,  there is a high demand for monitoring & inspection solutions for production and testing purposes in the electronics, automotive, and semiconductor sectors. Moreover, high spending on research and development and supportive government policies and programs regarding the application of advanced manufacturing technologies are also supporting the growth of the SWIR market in this region.

The incorporation of AI in SWIR systems has brought forward newer applications and use cases such as Advanced Driver Assistance Systems (ADAS), 3D sensing, hydration monitoring, bruise detection and ripeness monitoring, and non-invasive diagnostics, among others.

field of view中文

e-con Systems has 20+ years of experience designing, developing, and manufacturing OEM cameras. That’s why we understand the nuances involved in selecting lenses with the right FOV for your application. We can expertly guide you through the entire process of selecting the lens rather than merely acting as a camera supplier.

The study involved four major activities in estimating the current size of the SWIR market. Exhaustive secondary research was done to collect information on the market, peer, and parent markets. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain through primary research. Both top-down and bottom-up approaches were employed to estimate the complete market size. After that, market breakdown and data triangulation were used to estimate the market size of segments and subsegments.

Critical applications for these cameras are in security & surveillance, and industrial inspection, where accuracy and reliability are the main players. The integration of the next-generation cooling technologies that will make these cameras more efficient and affordable will drive further adoption. Technological advancements are also making cooled SWIR imagers affordable, which is expected to fuel the market growth.

The global SWIR market is valued at USD 631 million in 2024 and is anticipated to reach USD 1,068 million by 2029, at a CAGR of 11.1% during the forecast period.

Extensive primary research was conducted after gaining knowledge about the current scenario of the SWIR market through secondary research. Several primary interviews were conducted with experts from the demand and supply sides across four major regions—North America, Europe, Asia Pacific, and RoW. This primary data was collected through questionnaires, emails, and telephonic interviews.

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FOVcalculator

The global shortwave infrared (SWIR) market size is estimated to be valued at USD 631 million in 2024 and is projected to reach USD 1,068 million by 2029, growing at a CAGR of 11.1% from 2024 to 2029.

Prabu is the Chief Technology Officer and Head of Camera Products at e-con Systems, and comes with a rich experience of more than 15 years in the embedded vision space. He brings to the table a deep knowledge in USB cameras, embedded vision cameras, vision algorithms and FPGAs. He has built 50+ camera solutions spanning various domains such as medical, industrial, agriculture, retail, biometrics, and more. He also comes with expertise in device driver development and BSP development. Currently, Prabu’s focus is to build smart camera solutions that power new age AI based applications.

The leading players operating in the SWIR market are Teledyne FLIR LLC (US), Leonardo DRS (US), Corning Incorporated (US), Allied Vision Technologies GmbH (Germany), and Collins Aerospace (US), among others.

Spectral Imaging offers a close insight into materials and their compilation. It acquires  data through various wavelengths, subsequently enabling the discovery and examination of materials with discrepancies, making it valuable in applications such as food & beverages, environmental monitoring, and medical research, among others.

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Most of the embedded camera applications require the FOV to be wider enough to cover a large viewing area. For instance, a fish-eye lens is characterized by wider FOV and larger depth of field (DOF) and hence is suitable for surveillance applications. On the other hand, for a zoom/telescopic application, you might require a normal/narrow FOV.

With increasing superior accuracy and insights acquired through spectral imaging than conventional methods of imaging, it is  becoming a tool for various industries from agriculture to environmental monitoring and security. Improvements to technology make SWIR affordable to be used in various industries. Increased demand for data-rich imaging fuels the fastest growth of spectral imaging in the SWIR market.

fov和焦距的关系

Integrating AI algorithms with SWIR technology has enhanced accuracy, speed, efficiency, and adoption in various applications. According to a recent International Association for Pattern Recognition (IAPR) report, AI-powered imaging systems have revolutionized multiple sectors, including healthcare, agriculture, and security.

Generally for a sensor, FOV refers to the diagonal measurement – which is called DFOV or Diagonal FOV. Horizontal FOV (HFOV) and Vertical FOV (VFOV) will vary based on the aspect ratio of the image sensor used.

All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources. All the parameters affecting the markets covered in this research study have been accounted for, viewed in detail, verified through primary research, and analyzed to obtain the final quantitative and qualitative data. This data has been consolidated and supplemented with detailed inputs and analysis from MarketsandMarkets and presented in this report. The following figure represents this study’s overall market size estimation process.

SWIR is useful in disaster management and response because of its ability to see through smoke, fog, dust, and certain materials, which are highly likely to block the view of emergency response personnel during disaster management operations. SWIR can provide clear images in low light conditions, helping emergency personnel to rescue individuals and assess damage in challenging environments. These cameras can also detect temperature variations, identifying hotspots in fires, among other disasters.

You also have an option to capture the same field of view with sensors of different size. This can be done using a lens with the appropriate focal length. As a result, the same FOV can be achieved using a small sensor with a short focal length lens and a large sensor with a long focal length lens.

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SWIR offers superior imaging details for applications such as semiconductor inspection, fruit ripeness monitoring, and surveillance, among others. Hence, it is increasingly used in various emerging applications. The development of more affordable, user-friendly SWIR systems also supports the growth of the market. The potential application of SWIR in consumer electronics is also expected to drive market growth in the near future.

And one of the most popular among those solutions is e-CAM130A_CUXVR_3H02R1 180° FOV camera – a synchronized multi-camera solution that can be directly interfaced with the NVIDIA® Jetson AGX Xavier™ development kit. This camera solution comprises of three 13 MP camera modules that are based on the 1/3.2″ AR1335 CMOS image sensor from onsemi®. These 4K camera modules are positioned inwards to create a 180° FOV as shown in the image below:

SWIR has enhanced vision and 3D sensing capabilities, thereby increasing visibility in low-light conditions and enhancing driver safety. Its high-resolution imaging supports ADAS (Advanced Driver Assistance Systems) in identifying objects with great precision. SWIR also has the ability to see through materials and detect thermal differences, which aids in understanding vehicle surroundings. This integration of 3D sensing and enhanced vision in the automotive sector is expected to drive market growth for SWIR systems.

The SWIR market has emerging applications due to the superior penetration and details offered by different SWIR systems. The development of more affordable and user-friendly SWIR is one of the drivers of the SWIR market.

Based on imaging type, the SWIR industry is segmented into spectral, thermal, and hyperspectral imaging. Spectral imaging is widely used in many applications due to its InGaAs sensors, which are widely available in the market.

The monitoring & inspection segment is anticipated to register the highest CAGR during the forecast period. The SWIR technology provides  images even in challenging conditions of low light and dust, and hence has universal applicability.