From small sensor modules to artificial intelligence - there are different technologies and image processing algorithms to allows drones to see. Each application has different requirements for the vision system and is dependent on the available space within the drone and the required image quality. Dr. Frederik Schönebeck of FRAMOS spoke at the VDI conference on "Civil Drones in Industrial Use" and described the criteria for applications in mapping, object recognition and navigation as well as the relevance of artificial intelligence for drones.
For accurate and instantaneous sub-nanometer interferometric measurements, even in the presence of vibration and motion, 4D Technology developed a micro-polarizer array. But now, the company is excited about the high performance and low cost of Sony's IMX250 micro-polarizer sensor. 4D Technology’s main target applications demonstrate how on-chip polarization can improve and deepen imaging results.
Drones are a popular and increasingly widespread product used by consumers as well as in a diversity of industrial, military and other applications. Historically fully under the control of human operators on the ground, they're becoming increasingly autonomous as the cameras built into them find use not only for capturing footage of the world around them but also in understanding and responding to their surroundings. Combining imaging with other sensing modalities can further bolster the robustness of this autonomy.
CMOS image sensor technology has turned into the new normal. Well, not entirely... For high-end resolutions above 50 Megapixels, users still require CCD imagers to acquire high-resolution images. But now, CMOS sensors are available with high and super-high resolution, and bring numerous benefits for developers of demanding applications in terms of quality, speed, pricing, and time-to-market.
The implementation of imaging and vision solutions can be a tough road to embark on. Expert guidance is always helpful to find the right path from technology to development, and from implementation to production. Sarah Wu of FRAMOS is such an expert who is devoting most of her time every day to helping customers devise solutions from a single image sensor all the way to entire embedded vision systems.
Clearly, from an end user experience, a noisy image is not a good image. This is an issue made more difficult because of the high sensitivity of the eye for the smallest of deviations. Also, for algorithms, noise leads to more efforts in analysis and less accuracy. For a camera manufacturer, the noise contains a plethora of information about the sensor and the electronic driving it. Thus, the noise is a developer’s best friend and if carefully analyzed will lead to the best possible camera design and implicitly to the best possible image for a given sensor and electronic components.
Image sensors are available on the market in a very broad variety in type, size and performance for nearly all levels of applications and needs. From consumer sensors to industrial detectors and imagers dedicated to specific tasks, there is a huge number of devices available off-the-shelf. But there are six good reasons to have a deeper look, if a customized sensor helps to solve your imaging challenge and to achieve your vision objectives the best possible way.
OLEDs are cutting-edge technology for video displays. These displays are paper thin, exhibit high brightness, operate at lower power, and are made from a solid Si-wafer substrate. How does this technology work, what are the advantages and which applications benefit?
Imaging solutions, whether Industrial, Automotive or Consumer, have all benefited from the dramatic increase in processing power, interface bandwidths and data storage in recent years.
Many customers pose the question about which sensor is exclusively the “best” for their industrial application. The ON Semiconductor’s PYTHON family of image sensors provides a broad portfolio of sensor devices.
The relevant information in many vision applications is encoded into the color of the scenery. This information in normal color cameras is extracted based on the three standard color channels; red, green and blue (RGB), respectively. This color reproduction technique is an approximation and it is often insufficient to reliably solve a given machine vision problem. Hyperspectral imaging overcomes this limitation by providing a greater number of spectral bands, while maintaining an adequate spatial resolution.
This article will go through the evolution of this technology and explain some of the benefits of it. It will help your decision on how to transition your current CCD design to use a Sony Exmor CMOS sensor.
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