Behind the Datasheet and Vision systems

Image sensors are an essential part of vision systems, and their integration into hardware and software can be a complex process. The key to successful integration is a robust and flexible interface between the hardware and software, which is typically achieved through the use of a driver.


A driver is a software component that acts as the counterpart to the hardware element, providing the system's software with access to the features of the image sensor. Drivers are often specific to a particular component and can be developed and provided by the hardware component manufacturer. They can also be specific to the operating system being used, with Linux being a popular choice due to its wide range of available drivers.


When selecting an image sensor for an embedded vision application, it's important for engineers to consider the available driver options for the sensor. Generic drivers can provide a good starting point, but they may not have all the features or functionality needed for the specific application. If a Linux driver exists for the sensor, this can save a significant amount of time and effort for the engineering team.


However, the process of selecting an image sensor doesn't end once the sensor is chosen. Engineers also need to consider the sensor's configuration parameters and operating modes, as well as the support provided by the sensor's manufacturer. These factors can have a significant impact on the performance and functionality of the vision system.


In conclusion, image sensors are a critical component of vision systems and their integration into hardware and software requires careful consideration. Engineers need to think about the available driver options, configuration parameters, and operating modes before and after selecting an image sensor to ensure that the vision system performs as expected.

Comments

Post a Comment

Popular posts from this blog

Are microLEDs the next big (small) thing?

Light-emitting diode (LED) technology has been around for decades, but the introduction of micro LEDs has changed the way we think about it. As the name suggests, micro LEDs are tiny versions of the regular LEDs engineers use in embedded systems. The main application areas for micro LEDs are displays of various shapes and sizes, from very small to very big. MicroLEDs are defined as LEDs smaller than 100 micrometers (um) in size. This site is significantly smaller than traditional LEDs, and it opens up new possibilities for applications. The main advantage of micro LEDs is their increased brightness and higher power efficiency compared to OLED or LCD-based displays. This makes them ideal for microdisplays, which are defined as very small displays used for near-eye applications (i.e. not direct view). These displays are usually under 1-inch in size, with high performance (in terms of resolution, brightness, and refresh rates). The manufacturing process of micro LEDs is challenging due to...
Read more

Safety and security in autonomous driving

The integration of autonomous technology in vehicles has brought about a new set of concerns, particularly when it comes to safety and security. As the industry moves towards higher levels of automation, it becomes increasingly important to ensure that cybersecurity measures are in place to protect both the vehicles and their passengers. One key standard that is being used in the automotive industry is ISO/SAE 21434, which provides a structured process for incorporating cybersecurity considerations into automotive products. This standard requires manufacturers and suppliers to demonstrate due diligence in implementing cybersecurity engineering and ensures that cybersecurity management is applied throughout the supply chain. The development of automated driving features also brings new challenges to safety. Historically, automotive electrical and electronic systems have been regulated according to the functional safety standard ISO 26262, which assures a high level of resilience in th...
Read more

Six cool and update autonomous technologies

 EVAA prevents plane crashes with its moral compass: NASA’s Resilient Autonomy team and the Federal Aviation Administration have developed the Expandable Variable Autonomy Architecture (EVAA) to avoid aviation accidents by giving aircraft autonomous capabilities. It can assist human pilots or act on its own and has already saved 11 lives according to Mark Skoog, principal investigator for autonomy research at NASA's Armstrong Flight Research Center. Autonomous tractors increase farm productivity: Autonomous farming can increase the efficiency of large industrial farms, by using self-operating tractors and other machinery, such as John Deere's Autonomous Tractor Concept, which uses GPS and sensor technology to navigate and perform tasks on the farm. Self-driving tractor-trailers fight driver fatigue: Self-driving tractor-trailers can help reduce the risk of accidents caused by driver fatigue, by using sensors and cameras to navigate the roads, and advanced algorithms to make dec...
Read more